CA2217184A1 - A method for processing real-time contrast enhanced ultrasonic images - Google Patents
A method for processing real-time contrast enhanced ultrasonic images Download PDFInfo
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- CA2217184A1 CA2217184A1 CA002217184A CA2217184A CA2217184A1 CA 2217184 A1 CA2217184 A1 CA 2217184A1 CA 002217184 A CA002217184 A CA 002217184A CA 2217184 A CA2217184 A CA 2217184A CA 2217184 A1 CA2217184 A1 CA 2217184A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/48—Diagnostic techniques
- A61B8/481—Diagnostic techniques involving the use of contrast agent, e.g. microbubbles introduced into the bloodstream
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
- A61B8/06—Measuring blood flow
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
- G01S15/89—Sonar systems specially adapted for specific applications for mapping or imaging
- G01S15/8906—Short-range imaging systems; Acoustic microscope systems using pulse-echo techniques
- G01S15/899—Combination of imaging systems with ancillary equipment
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/52—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00
- G01S7/52017—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S15/00 particularly adapted to short-range imaging
- G01S7/52053—Display arrangements
- G01S7/52057—Cathode ray tube displays
- G01S7/52071—Multicolour displays; using colour coding; Optimising colour or information content in displays, e.g. parametric imaging
Abstract
The present invention is a novel method for producing real-time colorized, contrast enhanced images from a sequence of grey-scale video images obtained during diagnostic ultrasound. The particular colorizing scheme varies according to which information parameter is desired to be displayed in realtime. The information parameters used to colorize a segment of video images include: time-to-arrival, duration of brightening, and absolute brightening. Time-to-arrival colorization depicts the time that a given pixel achieves a given intensity threshold. Duration of brightening depicts the time that a given pixel's intensity stays above a given threshold. Absolute brightening depicts various threshold values obtained by the region's pixels.
Description
W 096133655 PCTrUS96/05834 A METHOD FOR PROCESSING REAL-TIME CONTRAST ENHANCED
ULTRASONIC IMAGES
FIELD OF THE INVENTION
The present invention relates in general to a method for processing a sequence of contrast-enhanced ultrasonic images and, in particular, to a method for colorizing a sequence of diagnostic ultrasound images in real-time which are 10 characterized by one or more parameters.
BACKGROUND OF THE INVENTION
In the field of medical ~ gnnstic im~ging, it is known to produce images of a patient's organs/tissues and to analyze these images for the express purpose of 15 idenliryillg potential disease conditions. For this purpose, there is a number of diagnostic modalities that may be used to obtain such images. For example, it is known to use single photon emission co,l,~u~ed tomography ("SPECT"), positron emission tomography ("PET"), computed tomography ("CT"), magnetic resonance im~ging ("MRI"), angiography and ultrasound. An overview of these dirrele"~ modalities is 2 0 provided in: Cardiac Tm~in~ - ~ Companion to Braunwald's Heart Disease, edited by Melvin L. Marcus, Heinrich R. Schelbert, David J. Skorton, and Gerald L. Wolf (W. B.
S~lln~1~rs Co., Phil~lelphi~ 1991) W 096/33655 PCTrUS96/05834 One modality that has found particular usefulness is contrast enhanced ultrasound im~ging Briefly, this technique utilizes ultrasonic im~gin~, which is based on the principle that waves of sound energy can be focused upon a "region of interest"
("ROI") and reflected in such a way as to produce an image thereof. The ultrasonic 5 tr~n~ cer utilized is placed on a body surface overlying the area to be imaged, and sound waves are directed toward that area. The tr~n.~t1nc~r detects reflected sound waves and the attached scanner tr~n~l~tes the data into video images. The quality of the images produced are further enhanced by the use of a contrast agent during the imslginp session.
When ultrasonic energy is tr~n~mittecl through a substance, the amount of energy reflected depends upon the frequency of the tr~n.~mi~.~ion and the acoustic propertles of the substance. Changes in the substance's acoustic properties (e.g. variance in the acoustic impedance) are most prominent at the interf~ees of different acoustic density or colllplessibility, such as liquid-solid or liquid-gas. Consequently, when 15 ultrasonic energy is directed through tissue, organ structures generate sound reflection signals for detection by the ultrasonic scanner. These signals can be int~n~ified by the proper use of a contrast agent.
Contrast enhanced images have the property that the presence of contrast 2 0 in a particular ROI produces an image visually recognizable from surrounding regions that are not suffused with the agent. One example of this type of im~ing is myocardial contrast echocardiography ("MCE"). In MCE, an intravascular injection of a contrast agent washes into the patient's heart while, ~imlllt~neously, ultrasound waves are directed W 096/33655 PCT~US96105834 to and reflected from the heart - thereby producing a sequence of contrast enhanced echocardiographic images.
Conventional ultrasound in~ging is termed B-mode or "grey scale" and 5 the shades of grey are based upon the amplitude of the backsc~ttt~r uhich is tr~n~mitte~l back to the tr~n~ cer from each ROI. The employment of contrast agents aids in grey scale im~ging by increasing the backscatter in a particular region as a result of the introduction of a contrast agent having increased echogenicity. The areas in which the contrast agent is present will appear brighter in a grey scale image.
In Gormection with ultrasound im~gill~, "backscatter" is a measure of the echogenicity of a particular substance (i.e. tissue, contrast agent, and the like).
Backscatter coefficient is an independent measure of the echogenicity of a substance.
The degree of amplitude of b~k.~c~tter observed is dependent on incident intensity.
"~tten~ tion" is a measure of the scattering, reflection, and absorption of the ultrasonic energy by a particular substance whereby less of the energy passes entirely through that substance and beyond. If the ultrasound energy is significantly attenuated during its tr~n~mi~ion through a substance, it will ~limini~h the backscattering signal 2 0 posterior to that substance thereby causing the posterior region to appear dark, regardless of the backscatter coefficient of material in that region. This is termed "shadowing." The shadowing effect causes portions of the grey scale image to appear dark when, in fact, there actually is contrast agent present in the tissue. Significallt ~ttel~ tion does not W O 96/33655 PCTrUS96/05834 allow for true visualization of the contrast agent which appears in the tissue/organs -beyond the attenuating areas, and can lead to a false diagnosis.
The ~ ion effect can lead to mi.~ cl~Lion of the data when 5 images are post-processed. For example, the effect of ~ttt?n~l~tion on the posterior myocardial wall is clearly evidenced in Figures lA and lB. In each of the frames, the transducer is located at the apex of the sector. In Figure lA, the entire myocardium is visible. However, with the introduction of the contrast agent into the chamber in Figure lB, the posterior region becomes dark, even though it may actually be experiencing some 10 degree of perfusion with the agent.
Figures 2A-2D depict the problems associated with attenuation and how it may adversely impact the ability to make an accurate diagnosis. Figure 2A is a top cross-sectional view of heart muscle 10 being imaged by ultrasound waves 22 em~n~ting 15 from tr~n~c~ucer 20. Heart muscle 10 comprises three regions of interest - anterior region 12 (i.e. closest to the k~n~ leer and in front of heart chamber 18), lateral region 16, and posterior region 14 (i.e. furthest away from tr~n~ lcer 20 and where heart chamber 18 is positioned between region 14 and tr~n~(illcer 20.) These three myocardial regions 12, 14, and 16 are labelled for convenience sake as regions X, Y, and Z respectively. As the 2 0 contrast agent washes in to the chamber, the agent absorbs and reflects much of the ultrasound energy, preventing it from reaching region Y. Regions X and Z are unaffected by the ~ltçnll~tion.
W 096/33655 PCT~US96/0~834 From the detected wave reflections, graphs, such as shown in Figures 2B-2D, may be generated. These graphs represent the mean image intensity of a particular ROI as a function of time. Thus, in Figure 2B, a typical time-hlLellsily curve is shown for heart anterior region X. From time at zero (i.e. the extreme left hand side of the 5 graph) to m~xi,.,ll", 24, the increasing portion ofthis graph is due to the wash-in of contrast agent into anterior region X. At m~xi",ll", 24, the anterior region X reaches its greatest concentration of contrast agent. From maximum 24 until time at infinity, the gradual decreasing hlLensiLy is due prim~rily to the wash-out of contrast agent (i.e.
decreasing concentration of contrast agent as the heart pumps through blood not imbued 10 with contrast agent) from anterior region X. The time-intensity curve for the region of interest indicates that region X is normal, healthy tissue.
Figure 2D depicts lateral region Z of heart 10 that might be characterized by a disease condition, such as ischemia, where the blood circulation to tissue in region Z
15 is less than optimal. Because the blood flow is not optimal, it can be seen that m~ximllm 27 is lower than the m;lxi~ ." 24 in region X and that the time to m~imnm in region Z
is greater than the time to m~xi",l"" in region X. Region Z, known to be unaffected by nll~tion~ shows a delay in both the time and hlLt;~ y of the contrast agent. This indicates an abnormality in that ROI.
The time-intensity graph in Figure 2C, although similar to the graph in Figure 2D, exhibits the effects of shadowing, resulting from ~ "~ ;on. Assuming that posterior region Y is as healthy as region X, the "actual" profiles of hllell~ily should be approximately the same ~ ion effects excepted. Thus, if region Y were anterior as opposed to posterior to the tr~n.~ cer, one would expect dotted profile 25 to appear as the time-intensity curve. However, in actuality, as the anterior chamber 18 fills with contrast agent prior to perfusion in anterior region Y, the contrast agent in chamber 18 5 ~ s most of the ultrasound energy that might have penetrated and scattered off of region Y once it has perfused. Thus, as seen in Figure 2C, the intensity of region Y
drops off to almost zero regardless of whether perfusion occurs in that region. Region Y
shows the effect of ~ttenll~tion on otherwise healthy tissue.
At some time after chamber 18 reaches its m~xi",l~". concentration of conkast agent, the effects of ;. ~ ion begin to wear off and the intensity in region Y
begins to increase. However, a trained diagnostician would note that the maximum intensity in region Y is lower than for region X and occurs later in time than for region X. This response is similar to the response given for fli~e~ee~1 region Z. Thus, the 15 potential to falsely diagnose region Y as rli~e~ed - while merely witnes~in~: the effects of nll~tion - exists.
While colorization of ultrasound images has previously been used to determine where contrast agent may have appeared in the tissues, these uses have not 2 0 effectively dealt with the problems of attenuation. In the article entitled "Quantification of Images Obtained During Myocardial Contrast Echocardiography", published in Echocardio~raphy: A Journal of CV Ultrasound & Allied Tech. (Vol 11, No. 4, 1994)~
pages 385-396, authors Jayaweera et al. review methods of quantifying two-dimensional W O 96/3365~ PCTrUS96/05834 grey scale echocardiographic images obtained during MCE. Specifically~ Jayaweera e~
al. disclose methods for obtaining time-intensity curves from MCE images. As well, they discuss enh~ncin3~ images by means of color-coding algo~ ls that reflect the degree and extent of enhancement.
Color-coding techniques that helpful for visn~li7ing the degree and extent of enhancement for a diagnostician, because the human eye is only able to discern a limited number of shades of grey, but has a much greater capacity to ~ rrimin~te between various colors. To accomplish this, Jayaweera et al. digitally subtract pre-10 contrast images from contrast-enh~nee(l images. In their plert;lled mode, three gated pre-contrast images are aligned and then averaged. The same is done for three gated contrast-enh~nred images. The averaged pre-contrast image is then subtracted from the averaged contrast-enh~nce~l image to yield one final post-processed frame.
For MCE color-coding, Jayaweera et al. have the operator define the endocardial and epicardial outlines in the digitally subtracted image. A histogram of grey scale intensities is then generated from the myocardial region within these outlines, and the digitally subtracted image is re-scaled over the entire dynamic range of the computer system followed by color coding. The color-coding operation is performed 2 0 only within the myocaldiu~ll defined by the endocardial and epicardial bonn-l~ries.
Thus, colorization in Jayaweera et al. is used primarily as a post-processing step after all video images have been captured. It is based upon the digital subtraction of pre-contrast from post-contrast frames and not upon time-intensity curves. This method may be used W O 96/33655 PCTrUS96/05834 to create an end image which shows areas where contrast agent either did or did not appear.
In an article entitled "Digital Subtraction Myocardial Contrast 5 Echocardiography: Design and Application of a New Analysis Program for Myocardial Perfusion Tm~ging", published by the Journal of the ~me~ican Society of Echocardio~raphy. July-August 1994, pages 355-362, authors ~lm~nn et al. describe another method for color-coding video echocardiographic images by first obtaining a simple time-intensity curve and then calculating and color-coding various parameters.
10 The time-intensity data generated reflects the wash-in, peak and the wash-out rates (i.e.
that portion of the time-intensity curve prior to, during and after maximum intensity, respectively) of contrast-agent enhanced blood from a particular ROI. Once time-intensity data is captured from the set of images, ~lm~nn et al. use this data to extract several parameters that enable evaluation of the ROI. Such parameters include: the slope 15 ofthe curve at any point; m;lxi,.~l~", h.~ellsi~y and the time to achieve it; the width ofthe time-intensity curve; and the area under any defined region of the curve. These parameters may be used to quantify the extent of blood flowing through the ROI.
The method disclosed by ~lm~nn et al. is similar to that described by 2 0 Jayaweera et al. in that the colorization is done as a post-image capture processing step -i.e. after all frames have been recorded and digital subtraction of the frames of interest has been accomplished; thus, yielding a single, colorized image as an end-result. Neither W 096/33655 PCT~US96/OS834 of the two methods described capture the useful parameters which can only be appreciated by viewing processed images in real-time.
By using colorization merely as a static, post-capture processing step, 5 very valuable information is lost that might otherwise be useful to detect dynamic tissue/organ function and conditions. These dynamic conditions may be noticeable only by viewing real-time colorized video sequences. One example of such a dynamic variable is "time-of-arrival" data - i.e. visual data showing the actual arrival time of contrast perfusion into a ROI in a particular organ. The time of arrival is an important 10 diagnostic parameter as it may be used to identify a clinically significant stenosis of an artery. In such a case. there is a reduced blood flow rate through the artery, so that the contrast agent a~e~lce is delayed in reaching the ROI.
Without a "time-of-arrival" parameter, the problem of attenuation is not 15 likely to be noted, as in a single post-processed colorized image. This is especially true for the pfior colorization methods of ~lm~nn et al. because their time-intensity curves have been averaged ovel a region and may include portions of the region which are artificially low or late due to the ;tll~"l~l;on effect.
2 0 Colorization pelrolllled according to the methods described by Jayaweera et al. or ~lm~nn et al. do not adequately compensate for ~1ten~l~tion and its effects.
Neither of the two prior methods describe any provision for detecting shadowing.
Therefore, colorization of a shadowed region is not colored in a dirr~ ll manner from a non-shadowed region. For example, colorization by arrival time would color a shadowed region and an i~r.htomic region similarly, although the reasons for the delay in appearance in the two regions are quite dirr~ . Thus, a trained cardiologist might falsely conclude that myocardial function is outside of normal parameters.
Real-time colorized video aids in the spotting of ;lllr.~ on by 1) the ability to view the tissue prior to the introduction of the contrast agent, and 2) the simultaneous shadowing of the posterior tissue as the contrast agent washes into the chamber region. While viewing the images in real-time, it is possible to see the first 10 frames and note the a~e~ ce of the tissue just prior to the arrival of the contrast agent.
A subsequent rapid decrease in the brightne~ of the tissue concurrent with the wash-in ofthe contrast agent into the chamber would be recognized as the result of ~ r...l.~1ion and not of tissue abnormality. Without the ability to see these two things, as is lacking in a single post-processed frame, the clinician would have to guess as to whether the 15 processed image indicates normal tissue which has been shadowed due to ~ttPnll~tion or whether tissue damage is present.
Thus, it is desirable to develop a method of producing real-time colorized ultrasoulld images to minimi7e the possibilities of false diagnoses and, in particular, to 2 0 identify ~tt~nllsltion and its effects as the im~ging occurs.
W O 9613365~ PCTrUS96/05834 Therefore, it is an object of the present invention to provide a method of producing real-time colorized ultrasound images that can visually depict ~ 1 ;on and its effects.
It is another object of the present invention to provide a method of producing real-time colorized ultrasound images that can be easily viewed and analyzed by trained diagnosticians.
It is yet another object of the present invention to provide colorized ultrasound images char~ct~ri7~cl by a variety of parameters in order to highliEht dirrer~
diagnostic aspects of the patient's organs.
CA 022l7l84 l997-l0-24 W 096/33655 PCTrUS96/05834 SUMMARY OF THE INVENIION ~
The present invention is a novel method for producing real-time colorized, contrast enhanced images from a sequence of grey-scale video images. The particular 5 colorizing scheme varies according to which information parameter is desired to be displayed in real-time. The information parameters used to colorize a segment of video images include: time-to-arrival, duration of brightçnin~, and absolute (degree of) briphtening Time-to-arrival colorization depicts the time that a given pixel achieves a given intensity threshold. A later time to threshold for a given pixel is colored dirr~cllLly than pixels that achieve threshold a predet~rmined amount of time before or after that later time. Duration of hrightPning depicts the time that a given pixel's intensity stays above a given threshold. The longer a pixel stays at or above threshold, 15 the pixel is given a dirr~ color at certain predetrrmined time periods. Thus, a pixel of long threshold duration is colored several times during the video image sequence.
Absolute brightçning depicts various threshold values obtained by the region's pixels.
Each color represents a dirr~lGllL threshold intensity. Thus, a particularly bright pixel may be colored several times during the course of a video sequence.
One advantage to viewing processed images in real-time is that the patient is still in a position for further testing which can be done immeAi~tely in the same session. There is clear benefit to obtaining useful information while the exam is in .
W 096/33655 13 PCT~US96/05834 progress rather than at some later time. Furthermore, the diagnostician can sooner decide on a course of therapy.
Yet another advantage to real-time processing is the detection of 5 ~ on in an im~ging session. This is important because ~lle"ll~lion and its effects can also lead to mi~ clalion of the data when images are post-processed.
Other features and advantages of the present invention will be a~pd.ellt from the following description of the pler~ d embo-iiment~, and from the claims.
For a full underst~n-iing of the present invention, reference should now be made to the following detailed description of the plt;rt;ll~d embo-limPnt~ of the invention and to the accol"p~,yi,lg drawings.
The file of this patent contains at least one drawing executed in color.
Copies of this patent with color drawings will be provided by the Patent and Tr~clem~rk Of fice upon request and payment of the necessary fee.
Figure l depicts the ~tt~nll~tion affect as contrast agent enters the chamber of the heart.
CA 022l7l84 l997-l0-24 W O 96/33655 PCTrUS96/05834 Figures 2A, 2B, 2C, and 2D depict the problem of ~1tenll~tion found in ultrasound im~ging of posterior regions of the heart.
Figure 3 depicts the manner in which ultrasound images are taken of a 5 patient's heart by an ultrasound image processor that is used in accordance with the principles of the present invention.
Figure 4 is a high level block diagram of one embodiment of an image processor unit that is used in accordance with the principles of the present invention.
Figures 5-7 depict a flow chart of the presently claimed real-time colorization method.
Figures 8A-8F depict the real-time colorization of a patient's heart using 15 the "time-of-arrival" parameter.
Figure 9 depicts a single frame of a real-time colorized image according to the "duration of bri~ht~onin~" parameter without the left ventricle colorized.
2 0 Figure 10 depicts an end-systolic real-time image frame colorized according to the "absolute brightrninP " parameter without the left ventricle colorized.
Figure 11 depicts an end-diastolic real-time image frame colorized according to the "absolute hright~nin~" parameter with the left ventricle colorized.
5 DETAILEI) DESCRIPTION OF THE INVENTION
Ultrasound im~in~ systems are well known in the art. Typical systems are m~mlf~hlred by, for example, Hewlett Packard Co~l~pal~y, Acuson, Inc.; Toshiba America Medical Systems, Inc.; and Advanced Technology Laboratories. These systems are employed for two-dimensional im~ging Another type of im~ging system is 10 based on three-~limen~ional im~ing An example of this type of system is mslmlf~ctured by, for example, TomTec Tm~ging Systems, Inc. The present invention may be employed with either two--limen~ional or three--limen~ional im~in~ systems.
Likewise, ultrasound contrast agents are also well-known in the art. They include, but are not limited to liquid emulsions, solids, enc~ps~ tetl fluids, encapsulated biocompatible gases and combinations thereof. Fluorinated liquids and gases are especially useful in cullLld~L compositions. The gaseous agents are of particular importance because of their efficiency as a reflector of ultrasound. Resonant gas bubbles scatter sound a thousand times more efficiently than a solid particle of the same size.
2 0 These types of agents include free bubbles of gas as well as those which are encapsulated by a shell m~teri~l The contrast agent may be ~timinictered via any of the known routes.
These routes include, but are not limited to hlLldv~illous (IV), hlLl~llu~cular (IM), intraarterial (IA), and intracardiac (IC).
CA 022l7l84 l997-l0-24 W 096/33655 PCTrUS96/05834 It is appreciated that any tissue or organ that receives a flow of blood may have images processed in the manner of the invention. These tissues/organs may include, but are not limited to the kidneys, liver, brain, testes, muscles, and heart.
Numerous parameters may be depicted by the colori_ation technique.
Among the parameters that may be characteri7~1 are those of the inst~nt~neous degree of bri~htt?nin~, the integrated degree of brighteninp, the duration of the brightening, and the time-of-arrival of the contrast agent.
One advantage in showing time-of-arrival data to a trained clinician is to Illillillli7.f~ the risk of producing a false negative diagnosis. For example, the post-image capture, colori_ation methods described by the above articles merely give a final picture depicting which areas of tissue were perfused at any time during the im~ging session.
15 Thus, if any tissue in the ROI were experiencing some latent perfusion deficiencies, whereby the arrival of the contrast agent were delayed, this condition would go n~l~tecte(l in the above mentioned methods.
For example, in the case of a critical stenosis or an occlusion of the 2 0 coronary artery, the "hibern~ting" myocardial region may receive contrast through a collateral blood supply. In this case, there is a longer path for the contrast agent to reach the myocardial region. The diagnosis of hibern~ting tissue is critical because it is widely believed that once the occlusion is elimin~te~l, there is an immediate return of normal CA 022l7l84 l997-l0-24 U'O 96133655 17 PCTrUS96/0~834 function. Therefore, the time-of-arrival information would be of significant clinical importance.
A false positive diagnosis might arise because some tissue, even though 5 normally perfused, might appear shadowed due to the effect of ~ttem~tion. Thus, a trained diagnostician might falsely conclude that the tissue is functioning outside normal parameters, when the problem is merely the result of the ~tteMIl~tion effect.
Furthermore, by colorizing based on data from a region which may have 10 portions affected by ~ l ion and shadowing, colors may be derived that do not kuly reflect the conkrast perfusion. Without such real-time, dynamic data, it is possible that even a trained ~ gnostician might falsely conclude that the tissue is functioning in a particular m~nner, either normally or abnormally. In these methods, there lies risk for both false negative and false positive diagnoses. Real-time colorization avoids these 1 5 dangers.
EXAMPLE - Myocardial Contrast Echocardiography Referring now to Figure 3, a cut-away view of patient 30 attached to echocardiographic k~n~ cer 36 is shown. A transducer is placed on the patient, 2 0 proximate to heart muscle 32. An injection (34) of conkast agent is made into the patient's vein so that the conkast agent reaches the heart and interacts with the ulkasound waves generated by k~n~ er 36. Sound waves reflected and detected at kansducer 36 are sent as input into image processing system 38.
CA 022l7l84 l997-l0-24 W 096/33655 PCTrUS96/05834 As the contrast agent enters into various heart regions, image processing system 38 detects an increased amplitude in the reflected ultrasound waves, which is characterized by a bright~nin~ of the image. Tissue areas that do not hright~n when 5 expected may indicate a disease condition in the area (e.g. poor or no circulation, necrosis or the like).
Referring now to Figure 4, an embodiment, in block diagram form, of image processing system 38 is depicted. Image processing system 38 comprises 10 diagnostic ultrasound scanner 40, optional analog-to-digital co~lv~ l~;. 42, image processor 44, digital-to-analog converter 56, and color monitor 58. Ultrasound scanner 40 encomp~es any means of r~ tinE ultrasound waves to the region of interest and detecting the reflected waves. Scanner 40 could comprise tr~n~ cer 36 and a means of producing electrical signals in accordance with the reflected waves detected. It will be 15 appreciated that such scanners are well known in the art.
The electrical signals generated by scanner 40 could either be digital or analog. If the signals are digital, then the current embodiment could input those signals into image processor 44 directly. Otherwise, an optional A/D conv~ , 42 could be used 2 0 to convert the analog signals.
Image processor 44 takes these digital signals and processes them to provide real-time colorized video images as output. The current embodiment of image W 096/3365S PCTrUS96/0~834 processor 44 comprises a central procPc~ing unit 46, trackball 48 for user-supplied input of prel1~fin~cl regions of interest, keyboard 50, and memory 52. Memory 52 may be large enough to retain several video images and store the colorization method 54 of the present invention. CPU 44 thus colorizes video images according to stored colorization 5 method 54.
After a given video image is colorized by image processor 44, the video image is output in digital form to D/A cc,llv~lL~ 56. D/A converter thereby supplies color monitor 58 with an analog signal capable of rendering on the monitor. It will be 10 appreciated that the present invention could ~ltern~tively use a digital color monitor, in which case D/A converter 56 would be optional.
Having described a current embodiment of the present invention, the colorization method of the present invention will now be described. Figures 5-7 are 15 flowcharts describing the colorization method as ~ ly embodied. Preliminary processing begins in Figure 5 at step 62. The opc;ld~l-user selects which point in the cardiac cycle at which the series of video images will be taken. The same point in the cycle is used to reduce the amount of heart distortion from frame to frame because the heart is presumably in the same place at the same point in the cardiac cycle. Of all the 2 0 point in the cardiac cycle, the most frequently used are the end-systolic and the end-diastolic points.
W 096/33655 PCTrUS96/05834 The O1JG1~O1 then selects the region of interest to be colorized (C-ROI) in the heart at step 66. This may be accompli~hecl by allowing continuous sc~nning of the heart prior to ~lnnini.~t~.ring the contrast agent and having the operator select the C-ROI
on screen with trackball 48. Once selected, the current method allows other points on the 5 cycle to be included in the analysis at step 68.
Once all the point on the cycle and C-ROI's have been identified, the operator selects a "trigger" region of interest (T-ROI) that is used to identify that the contrast agent has or will be imminently entPrin~ entered the region of interest. For 10 ~.cses~ing myocardial perfusion, a most advantageous T-ROI would be somewhere in the heart chamber because the heart chamber receives the contrast agent prior to the muscle.
For rx;l~llillillg the left ventricle, the T-ROI may be in the right ventricle or the left atrium. Once the T-ROI is selected, the heart continues to be imaged frame-by-frame.
As each frame is acquired, the current method ~letermines whether the current frame is one of the pre-identified points of the cardiac cycle. This may be accomplished by pGlrollllil~g an electrocardiogram (ECG) on the patient at the same time that the image sequence is being captured. The ECG could then be used to supply steps 74 and 76 the data needed to ~1et~.rmine the exact point in the cardiac cycle.
If the current frame is processed at step 78, the hllellsily of each pixel is acquired in the C-ROI and the T-ROI. This hll~ y pixel data is stored and used to .
CA 022l7l84 l997-l0-24 96/33655 PCTrUS96/05834 compute an average intensity over several baseline frames. In the current method, two or three baseline frames are used and that number is tested in step 82.
At steps 84 and 86, the current method waits until there is a m~rk~l 5 change in intensity in a sufficient number of pixels in the T-ROI. This change denotes that the contrast agent has been a-lmini~tered and that the next frame is the first non-baseline frame. The first non-baseline frame is processed at step 90 in Figure 6. In step 90, for each pixel in the C-ROI, a slope and intercept of pixel intensity vs. time for the baseline frames is calculated. From this slope and h~ lsily, the baseline intensity for the 10 current frame is estim~te(l in step 92.
This method to estim~te the baseline hlL~l~ily for post-contrast frames uses the hllen,ily from pre-contrast frames. The intensity from pre-contrast frames may be simply averaged to obtain a value for baseline frames that is constant for all 15 sllc cee~ling frames. A simple average may not be sufficient in some cases to characterize the baseline as some changes in the pixel intensity may occur prior to the arrival of contrast. These changes may arise, for example, from poor image registration caused by changes in the tr~n~ cer position and/or the motion of the heart or the ROI may be adjacent to a region where contrast has arrived (e.g. the septal region of the myoc~L..li~n lying next to the right ventricle, which receives a high concentration of contrast prior to the left ventricle). In these cases, the baseline intensity is better represented by a line, which assumes that the changes will continue over time, incorporating a time dependence on the baseline intensity.
CA 022l7l84 l997-l0-24 W 096/33655 22 PCTrUS96/05834 With the b~eline hlLellsi~y calculated for each pixel, the pixel intensity is calculated by subtracting the estim~tecl baseline from the observed hl~el~ y. Once the pixel intensity has been calculated, the parameter of interest is then calculated in step 96.
5 As will be discussed below, the parameter of interest may be one of many that relate the intensity of the pixel into the time of the observed intensity. Cul~c;llLly, these parameters include time-to-arrival data, duration of hri htf-nin~, and absolute brightening For each pixel in the C-ROI, the calculated parameter is used to find the 10 particular color that the pixel receives in the current frame. The particular color may be found in a color look-up table. In this manner, a colorized image frame is produced for the first non-baseline frame in step 102. This first colorized frame produces an initial coloring for each pixel that subsequent frames may change.
S~lccee~ling frames are processed starting at step 104 in Figure 7. Again, the image sequence is tested for images that occur at the same point in the cardiac cycle at steps l 06 and l 08. If the frame is to be processed, pixel intensity is acquired, a new pixel baseline is estim~t~-l the pixel intensity is baseline subtracted, and the pararneter of interest is calculated in steps l l 0 through l l 6. At step l l 8, the current pixel intensity is 2 0 compared with the intensity in the last frame. If the current intensity value is less, then the previous color is determined in step 120. If greater, a new color is looked-up in the table. In this manner, subsequent frames are colorized and produced in step 124. Lastly, .
the current method looks for user-supplied tprrnin~tion in step 126 to complete the colorization process.
To gain a better lmt1Pr~t~n~lin~ of the application of the above-described 5 colorization method, Figures 8A-8F show a series of six frames that have been colorized using the time-to-arrival parameter. Thus, individual pixels are colored when they meet or exceed a certain hllellsily threshold at a specific time - otherwise the pixel remains uncolored. Under the current embodiment of this parameter, pixels are colored yellow if they exceed threshold within a certain time, tl; green if they have exceeded threshold 10 between time tl and another time t2; blue if threshold occurs between t2 and a later time t3; and red if threshold occurs between t3 and a later time t4.
Figures 8A-8F also depicts how the real-time colorized image processing of the present invention can make visual for the ~ gnostici~n the effects of ~ttenll~tion.
15 This particular series of real-time colorized images of exhibits both the effects of ~tt~ml~tion and a possible disease condition in the patient's heart.
Figure 8A is the first frame in the series and is taken prior to the arrival of the contrast agent; thus, no color is added to the frame. At the time of Figure 8B, time 2 0 has elapsed to somewhere between tl and t2, as defined above, because the colors yellow and green are now visible. At this time, it is clear that perfusion all around the heart muscle is occurring - even in the posterior region of the heart, since some of the posterior W O 96/33655 PCTrUS96/05834 area has been colored yellow. It should be noted that because the color yellow is fairly well distributed about the heart muscle, the effects of ~ttenll~tion are not yet present.
By the time of Figure 8C (i.e. somewhere between t2 and t3), the effects of 5 ~ttenU~tion are beginning to show. The colors blue and green are now predominant in the hemi~phere anterior to the heart chamber; whereas the posterior hemisphere is largely yellow or uncolored. Also noted in Figure 8C is a potentially ~lise~e~l region to the right of the heart chamber and in the anterior hemisphere - this region remains uncolored.
In Figure 8D, the current time is somewhere after t4, as the color red has now appeared. As the red predomin~tes in the posterior region, together with some uncolored pixels, the region is still "shadowed" by agent in the heart chamber. Both Figures 8E and 8F are likewise after time t4. By the time of Figure 8F, the vast majority of the posterior region is colorized - with red as predominant color. This coloring pattern 15 is con~i~t~nt with the expected effects of ~ ion and is made plainly visual to the diagnostician.
Additionally noted in Figures 8E and 8F, the right lateral region has been colorized red. This red colorization cannot be e~pl~ined away as due to the effects of 2 0 ~ttenll~tion. The only other plausible explanation for the late "time-to-arrival" threshold is that there is some restriction in the flow of blood to this particular region - potentially a diseased condition.
W O 96/336SS 25 PCTrUS96/05834 The images presented in Figures 8A-8F are frames that have been chosen from the real-time moving video sequence for purposes of representing the salient aspects of the invention. It can be appreciated that the present invention lies in viewing the video image as a flowing sequence of colorized frames appearing on the monitor in 5 real-time.
Other parameters are similarly depicted. Figure 9 depicts a single frame in a sequence of real-time images colorized according to the "duration of bri~htt?ning"
parameter. As noted, tbis particular color scheme uses color to denote how long a given 10 pixel was above a certain threshold. If the period of time is long, the color of the pixel is red. If the pixel was at or above the threshold for only a short period of time, the color is blue.
Figures 10 and 11 both depict a frame colorized according to the "absolute 15 bri~htening" parameter. Absolute hri3~ht~ning colors a particular pixel according to the level of intensity it has achieved. This may be accomplished by pre~1efining a set of threshold levels that are assigned dirrtlcll~ colors. If the given pixel meets a given threshold, it is assigned that particular color. The color is re~sipned only if the pixel exceeds another threshold.
It will be noted that, in some frames, the left ventricle chamber is not colorized. In some cases, it may be desirable to color the left ventricle. For example, W 096/33655 PCT~US96/05834 26 Figure 10, is an end-systolic frame without the left ventricle colored; whereas Figure 1 1 is an end-diastolic frame with the left ventricle colored.
Although only four parameters have been discussed in connection with 5 the present colorization method, it will be appreciated that more parameters that relate pixel intensity to a time element is possible and that the present invention should not be limited to the above-described parameters. Indeed, the present invention should be construed to cover any parameter that is reasonably compatible with the above-described colorization method.
There has thus been shown and described a novel method for the processing of real-time contrast enhanced, colorized images which meets the objects and advantages sought. As stated above, many changes, modifications, variations and other uses and applications of the subject invention will, however, become a~p~ ll to those 15 skilled in the art after considering this specification and accolll~ yhlg drawings which disclose pler~lled embodiments thereof. All such changes, modifications, variations and other uses and applications which do not depart from the spirit and scope of the invention are deemed to be covered by the invention which is limited only by the claims which follow.
ULTRASONIC IMAGES
FIELD OF THE INVENTION
The present invention relates in general to a method for processing a sequence of contrast-enhanced ultrasonic images and, in particular, to a method for colorizing a sequence of diagnostic ultrasound images in real-time which are 10 characterized by one or more parameters.
BACKGROUND OF THE INVENTION
In the field of medical ~ gnnstic im~ging, it is known to produce images of a patient's organs/tissues and to analyze these images for the express purpose of 15 idenliryillg potential disease conditions. For this purpose, there is a number of diagnostic modalities that may be used to obtain such images. For example, it is known to use single photon emission co,l,~u~ed tomography ("SPECT"), positron emission tomography ("PET"), computed tomography ("CT"), magnetic resonance im~ging ("MRI"), angiography and ultrasound. An overview of these dirrele"~ modalities is 2 0 provided in: Cardiac Tm~in~ - ~ Companion to Braunwald's Heart Disease, edited by Melvin L. Marcus, Heinrich R. Schelbert, David J. Skorton, and Gerald L. Wolf (W. B.
S~lln~1~rs Co., Phil~lelphi~ 1991) W 096/33655 PCTrUS96/05834 One modality that has found particular usefulness is contrast enhanced ultrasound im~ging Briefly, this technique utilizes ultrasonic im~gin~, which is based on the principle that waves of sound energy can be focused upon a "region of interest"
("ROI") and reflected in such a way as to produce an image thereof. The ultrasonic 5 tr~n~ cer utilized is placed on a body surface overlying the area to be imaged, and sound waves are directed toward that area. The tr~n.~t1nc~r detects reflected sound waves and the attached scanner tr~n~l~tes the data into video images. The quality of the images produced are further enhanced by the use of a contrast agent during the imslginp session.
When ultrasonic energy is tr~n~mittecl through a substance, the amount of energy reflected depends upon the frequency of the tr~n.~mi~.~ion and the acoustic propertles of the substance. Changes in the substance's acoustic properties (e.g. variance in the acoustic impedance) are most prominent at the interf~ees of different acoustic density or colllplessibility, such as liquid-solid or liquid-gas. Consequently, when 15 ultrasonic energy is directed through tissue, organ structures generate sound reflection signals for detection by the ultrasonic scanner. These signals can be int~n~ified by the proper use of a contrast agent.
Contrast enhanced images have the property that the presence of contrast 2 0 in a particular ROI produces an image visually recognizable from surrounding regions that are not suffused with the agent. One example of this type of im~ing is myocardial contrast echocardiography ("MCE"). In MCE, an intravascular injection of a contrast agent washes into the patient's heart while, ~imlllt~neously, ultrasound waves are directed W 096/33655 PCT~US96105834 to and reflected from the heart - thereby producing a sequence of contrast enhanced echocardiographic images.
Conventional ultrasound in~ging is termed B-mode or "grey scale" and 5 the shades of grey are based upon the amplitude of the backsc~ttt~r uhich is tr~n~mitte~l back to the tr~n~ cer from each ROI. The employment of contrast agents aids in grey scale im~ging by increasing the backscatter in a particular region as a result of the introduction of a contrast agent having increased echogenicity. The areas in which the contrast agent is present will appear brighter in a grey scale image.
In Gormection with ultrasound im~gill~, "backscatter" is a measure of the echogenicity of a particular substance (i.e. tissue, contrast agent, and the like).
Backscatter coefficient is an independent measure of the echogenicity of a substance.
The degree of amplitude of b~k.~c~tter observed is dependent on incident intensity.
"~tten~ tion" is a measure of the scattering, reflection, and absorption of the ultrasonic energy by a particular substance whereby less of the energy passes entirely through that substance and beyond. If the ultrasound energy is significantly attenuated during its tr~n~mi~ion through a substance, it will ~limini~h the backscattering signal 2 0 posterior to that substance thereby causing the posterior region to appear dark, regardless of the backscatter coefficient of material in that region. This is termed "shadowing." The shadowing effect causes portions of the grey scale image to appear dark when, in fact, there actually is contrast agent present in the tissue. Significallt ~ttel~ tion does not W O 96/33655 PCTrUS96/05834 allow for true visualization of the contrast agent which appears in the tissue/organs -beyond the attenuating areas, and can lead to a false diagnosis.
The ~ ion effect can lead to mi.~ cl~Lion of the data when 5 images are post-processed. For example, the effect of ~ttt?n~l~tion on the posterior myocardial wall is clearly evidenced in Figures lA and lB. In each of the frames, the transducer is located at the apex of the sector. In Figure lA, the entire myocardium is visible. However, with the introduction of the contrast agent into the chamber in Figure lB, the posterior region becomes dark, even though it may actually be experiencing some 10 degree of perfusion with the agent.
Figures 2A-2D depict the problems associated with attenuation and how it may adversely impact the ability to make an accurate diagnosis. Figure 2A is a top cross-sectional view of heart muscle 10 being imaged by ultrasound waves 22 em~n~ting 15 from tr~n~c~ucer 20. Heart muscle 10 comprises three regions of interest - anterior region 12 (i.e. closest to the k~n~ leer and in front of heart chamber 18), lateral region 16, and posterior region 14 (i.e. furthest away from tr~n~ lcer 20 and where heart chamber 18 is positioned between region 14 and tr~n~(illcer 20.) These three myocardial regions 12, 14, and 16 are labelled for convenience sake as regions X, Y, and Z respectively. As the 2 0 contrast agent washes in to the chamber, the agent absorbs and reflects much of the ultrasound energy, preventing it from reaching region Y. Regions X and Z are unaffected by the ~ltçnll~tion.
W 096/33655 PCT~US96/0~834 From the detected wave reflections, graphs, such as shown in Figures 2B-2D, may be generated. These graphs represent the mean image intensity of a particular ROI as a function of time. Thus, in Figure 2B, a typical time-hlLellsily curve is shown for heart anterior region X. From time at zero (i.e. the extreme left hand side of the 5 graph) to m~xi,.,ll", 24, the increasing portion ofthis graph is due to the wash-in of contrast agent into anterior region X. At m~xi",ll", 24, the anterior region X reaches its greatest concentration of contrast agent. From maximum 24 until time at infinity, the gradual decreasing hlLensiLy is due prim~rily to the wash-out of contrast agent (i.e.
decreasing concentration of contrast agent as the heart pumps through blood not imbued 10 with contrast agent) from anterior region X. The time-intensity curve for the region of interest indicates that region X is normal, healthy tissue.
Figure 2D depicts lateral region Z of heart 10 that might be characterized by a disease condition, such as ischemia, where the blood circulation to tissue in region Z
15 is less than optimal. Because the blood flow is not optimal, it can be seen that m~ximllm 27 is lower than the m;lxi~ ." 24 in region X and that the time to m~imnm in region Z
is greater than the time to m~xi",l"" in region X. Region Z, known to be unaffected by nll~tion~ shows a delay in both the time and hlLt;~ y of the contrast agent. This indicates an abnormality in that ROI.
The time-intensity graph in Figure 2C, although similar to the graph in Figure 2D, exhibits the effects of shadowing, resulting from ~ "~ ;on. Assuming that posterior region Y is as healthy as region X, the "actual" profiles of hllell~ily should be approximately the same ~ ion effects excepted. Thus, if region Y were anterior as opposed to posterior to the tr~n.~ cer, one would expect dotted profile 25 to appear as the time-intensity curve. However, in actuality, as the anterior chamber 18 fills with contrast agent prior to perfusion in anterior region Y, the contrast agent in chamber 18 5 ~ s most of the ultrasound energy that might have penetrated and scattered off of region Y once it has perfused. Thus, as seen in Figure 2C, the intensity of region Y
drops off to almost zero regardless of whether perfusion occurs in that region. Region Y
shows the effect of ~ttenll~tion on otherwise healthy tissue.
At some time after chamber 18 reaches its m~xi",l~". concentration of conkast agent, the effects of ;. ~ ion begin to wear off and the intensity in region Y
begins to increase. However, a trained diagnostician would note that the maximum intensity in region Y is lower than for region X and occurs later in time than for region X. This response is similar to the response given for fli~e~ee~1 region Z. Thus, the 15 potential to falsely diagnose region Y as rli~e~ed - while merely witnes~in~: the effects of nll~tion - exists.
While colorization of ultrasound images has previously been used to determine where contrast agent may have appeared in the tissues, these uses have not 2 0 effectively dealt with the problems of attenuation. In the article entitled "Quantification of Images Obtained During Myocardial Contrast Echocardiography", published in Echocardio~raphy: A Journal of CV Ultrasound & Allied Tech. (Vol 11, No. 4, 1994)~
pages 385-396, authors Jayaweera et al. review methods of quantifying two-dimensional W O 96/3365~ PCTrUS96/05834 grey scale echocardiographic images obtained during MCE. Specifically~ Jayaweera e~
al. disclose methods for obtaining time-intensity curves from MCE images. As well, they discuss enh~ncin3~ images by means of color-coding algo~ ls that reflect the degree and extent of enhancement.
Color-coding techniques that helpful for visn~li7ing the degree and extent of enhancement for a diagnostician, because the human eye is only able to discern a limited number of shades of grey, but has a much greater capacity to ~ rrimin~te between various colors. To accomplish this, Jayaweera et al. digitally subtract pre-10 contrast images from contrast-enh~nee(l images. In their plert;lled mode, three gated pre-contrast images are aligned and then averaged. The same is done for three gated contrast-enh~nred images. The averaged pre-contrast image is then subtracted from the averaged contrast-enh~nce~l image to yield one final post-processed frame.
For MCE color-coding, Jayaweera et al. have the operator define the endocardial and epicardial outlines in the digitally subtracted image. A histogram of grey scale intensities is then generated from the myocardial region within these outlines, and the digitally subtracted image is re-scaled over the entire dynamic range of the computer system followed by color coding. The color-coding operation is performed 2 0 only within the myocaldiu~ll defined by the endocardial and epicardial bonn-l~ries.
Thus, colorization in Jayaweera et al. is used primarily as a post-processing step after all video images have been captured. It is based upon the digital subtraction of pre-contrast from post-contrast frames and not upon time-intensity curves. This method may be used W O 96/33655 PCTrUS96/05834 to create an end image which shows areas where contrast agent either did or did not appear.
In an article entitled "Digital Subtraction Myocardial Contrast 5 Echocardiography: Design and Application of a New Analysis Program for Myocardial Perfusion Tm~ging", published by the Journal of the ~me~ican Society of Echocardio~raphy. July-August 1994, pages 355-362, authors ~lm~nn et al. describe another method for color-coding video echocardiographic images by first obtaining a simple time-intensity curve and then calculating and color-coding various parameters.
10 The time-intensity data generated reflects the wash-in, peak and the wash-out rates (i.e.
that portion of the time-intensity curve prior to, during and after maximum intensity, respectively) of contrast-agent enhanced blood from a particular ROI. Once time-intensity data is captured from the set of images, ~lm~nn et al. use this data to extract several parameters that enable evaluation of the ROI. Such parameters include: the slope 15 ofthe curve at any point; m;lxi,.~l~", h.~ellsi~y and the time to achieve it; the width ofthe time-intensity curve; and the area under any defined region of the curve. These parameters may be used to quantify the extent of blood flowing through the ROI.
The method disclosed by ~lm~nn et al. is similar to that described by 2 0 Jayaweera et al. in that the colorization is done as a post-image capture processing step -i.e. after all frames have been recorded and digital subtraction of the frames of interest has been accomplished; thus, yielding a single, colorized image as an end-result. Neither W 096/33655 PCT~US96/OS834 of the two methods described capture the useful parameters which can only be appreciated by viewing processed images in real-time.
By using colorization merely as a static, post-capture processing step, 5 very valuable information is lost that might otherwise be useful to detect dynamic tissue/organ function and conditions. These dynamic conditions may be noticeable only by viewing real-time colorized video sequences. One example of such a dynamic variable is "time-of-arrival" data - i.e. visual data showing the actual arrival time of contrast perfusion into a ROI in a particular organ. The time of arrival is an important 10 diagnostic parameter as it may be used to identify a clinically significant stenosis of an artery. In such a case. there is a reduced blood flow rate through the artery, so that the contrast agent a~e~lce is delayed in reaching the ROI.
Without a "time-of-arrival" parameter, the problem of attenuation is not 15 likely to be noted, as in a single post-processed colorized image. This is especially true for the pfior colorization methods of ~lm~nn et al. because their time-intensity curves have been averaged ovel a region and may include portions of the region which are artificially low or late due to the ;tll~"l~l;on effect.
2 0 Colorization pelrolllled according to the methods described by Jayaweera et al. or ~lm~nn et al. do not adequately compensate for ~1ten~l~tion and its effects.
Neither of the two prior methods describe any provision for detecting shadowing.
Therefore, colorization of a shadowed region is not colored in a dirr~ ll manner from a non-shadowed region. For example, colorization by arrival time would color a shadowed region and an i~r.htomic region similarly, although the reasons for the delay in appearance in the two regions are quite dirr~ . Thus, a trained cardiologist might falsely conclude that myocardial function is outside of normal parameters.
Real-time colorized video aids in the spotting of ;lllr.~ on by 1) the ability to view the tissue prior to the introduction of the contrast agent, and 2) the simultaneous shadowing of the posterior tissue as the contrast agent washes into the chamber region. While viewing the images in real-time, it is possible to see the first 10 frames and note the a~e~ ce of the tissue just prior to the arrival of the contrast agent.
A subsequent rapid decrease in the brightne~ of the tissue concurrent with the wash-in ofthe contrast agent into the chamber would be recognized as the result of ~ r...l.~1ion and not of tissue abnormality. Without the ability to see these two things, as is lacking in a single post-processed frame, the clinician would have to guess as to whether the 15 processed image indicates normal tissue which has been shadowed due to ~ttPnll~tion or whether tissue damage is present.
Thus, it is desirable to develop a method of producing real-time colorized ultrasoulld images to minimi7e the possibilities of false diagnoses and, in particular, to 2 0 identify ~tt~nllsltion and its effects as the im~ging occurs.
W O 9613365~ PCTrUS96/05834 Therefore, it is an object of the present invention to provide a method of producing real-time colorized ultrasound images that can visually depict ~ 1 ;on and its effects.
It is another object of the present invention to provide a method of producing real-time colorized ultrasound images that can be easily viewed and analyzed by trained diagnosticians.
It is yet another object of the present invention to provide colorized ultrasound images char~ct~ri7~cl by a variety of parameters in order to highliEht dirrer~
diagnostic aspects of the patient's organs.
CA 022l7l84 l997-l0-24 W 096/33655 PCTrUS96/05834 SUMMARY OF THE INVENIION ~
The present invention is a novel method for producing real-time colorized, contrast enhanced images from a sequence of grey-scale video images. The particular 5 colorizing scheme varies according to which information parameter is desired to be displayed in real-time. The information parameters used to colorize a segment of video images include: time-to-arrival, duration of brightçnin~, and absolute (degree of) briphtening Time-to-arrival colorization depicts the time that a given pixel achieves a given intensity threshold. A later time to threshold for a given pixel is colored dirr~cllLly than pixels that achieve threshold a predet~rmined amount of time before or after that later time. Duration of hrightPning depicts the time that a given pixel's intensity stays above a given threshold. The longer a pixel stays at or above threshold, 15 the pixel is given a dirr~ color at certain predetrrmined time periods. Thus, a pixel of long threshold duration is colored several times during the video image sequence.
Absolute brightçning depicts various threshold values obtained by the region's pixels.
Each color represents a dirr~lGllL threshold intensity. Thus, a particularly bright pixel may be colored several times during the course of a video sequence.
One advantage to viewing processed images in real-time is that the patient is still in a position for further testing which can be done immeAi~tely in the same session. There is clear benefit to obtaining useful information while the exam is in .
W 096/33655 13 PCT~US96/05834 progress rather than at some later time. Furthermore, the diagnostician can sooner decide on a course of therapy.
Yet another advantage to real-time processing is the detection of 5 ~ on in an im~ging session. This is important because ~lle"ll~lion and its effects can also lead to mi~ clalion of the data when images are post-processed.
Other features and advantages of the present invention will be a~pd.ellt from the following description of the pler~ d embo-iiment~, and from the claims.
For a full underst~n-iing of the present invention, reference should now be made to the following detailed description of the plt;rt;ll~d embo-limPnt~ of the invention and to the accol"p~,yi,lg drawings.
The file of this patent contains at least one drawing executed in color.
Copies of this patent with color drawings will be provided by the Patent and Tr~clem~rk Of fice upon request and payment of the necessary fee.
Figure l depicts the ~tt~nll~tion affect as contrast agent enters the chamber of the heart.
CA 022l7l84 l997-l0-24 W O 96/33655 PCTrUS96/05834 Figures 2A, 2B, 2C, and 2D depict the problem of ~1tenll~tion found in ultrasound im~ging of posterior regions of the heart.
Figure 3 depicts the manner in which ultrasound images are taken of a 5 patient's heart by an ultrasound image processor that is used in accordance with the principles of the present invention.
Figure 4 is a high level block diagram of one embodiment of an image processor unit that is used in accordance with the principles of the present invention.
Figures 5-7 depict a flow chart of the presently claimed real-time colorization method.
Figures 8A-8F depict the real-time colorization of a patient's heart using 15 the "time-of-arrival" parameter.
Figure 9 depicts a single frame of a real-time colorized image according to the "duration of bri~ht~onin~" parameter without the left ventricle colorized.
2 0 Figure 10 depicts an end-systolic real-time image frame colorized according to the "absolute brightrninP " parameter without the left ventricle colorized.
Figure 11 depicts an end-diastolic real-time image frame colorized according to the "absolute hright~nin~" parameter with the left ventricle colorized.
5 DETAILEI) DESCRIPTION OF THE INVENTION
Ultrasound im~in~ systems are well known in the art. Typical systems are m~mlf~hlred by, for example, Hewlett Packard Co~l~pal~y, Acuson, Inc.; Toshiba America Medical Systems, Inc.; and Advanced Technology Laboratories. These systems are employed for two-dimensional im~ging Another type of im~ging system is 10 based on three-~limen~ional im~ing An example of this type of system is mslmlf~ctured by, for example, TomTec Tm~ging Systems, Inc. The present invention may be employed with either two--limen~ional or three--limen~ional im~in~ systems.
Likewise, ultrasound contrast agents are also well-known in the art. They include, but are not limited to liquid emulsions, solids, enc~ps~ tetl fluids, encapsulated biocompatible gases and combinations thereof. Fluorinated liquids and gases are especially useful in cullLld~L compositions. The gaseous agents are of particular importance because of their efficiency as a reflector of ultrasound. Resonant gas bubbles scatter sound a thousand times more efficiently than a solid particle of the same size.
2 0 These types of agents include free bubbles of gas as well as those which are encapsulated by a shell m~teri~l The contrast agent may be ~timinictered via any of the known routes.
These routes include, but are not limited to hlLldv~illous (IV), hlLl~llu~cular (IM), intraarterial (IA), and intracardiac (IC).
CA 022l7l84 l997-l0-24 W 096/33655 PCTrUS96/05834 It is appreciated that any tissue or organ that receives a flow of blood may have images processed in the manner of the invention. These tissues/organs may include, but are not limited to the kidneys, liver, brain, testes, muscles, and heart.
Numerous parameters may be depicted by the colori_ation technique.
Among the parameters that may be characteri7~1 are those of the inst~nt~neous degree of bri~htt?nin~, the integrated degree of brighteninp, the duration of the brightening, and the time-of-arrival of the contrast agent.
One advantage in showing time-of-arrival data to a trained clinician is to Illillillli7.f~ the risk of producing a false negative diagnosis. For example, the post-image capture, colori_ation methods described by the above articles merely give a final picture depicting which areas of tissue were perfused at any time during the im~ging session.
15 Thus, if any tissue in the ROI were experiencing some latent perfusion deficiencies, whereby the arrival of the contrast agent were delayed, this condition would go n~l~tecte(l in the above mentioned methods.
For example, in the case of a critical stenosis or an occlusion of the 2 0 coronary artery, the "hibern~ting" myocardial region may receive contrast through a collateral blood supply. In this case, there is a longer path for the contrast agent to reach the myocardial region. The diagnosis of hibern~ting tissue is critical because it is widely believed that once the occlusion is elimin~te~l, there is an immediate return of normal CA 022l7l84 l997-l0-24 U'O 96133655 17 PCTrUS96/0~834 function. Therefore, the time-of-arrival information would be of significant clinical importance.
A false positive diagnosis might arise because some tissue, even though 5 normally perfused, might appear shadowed due to the effect of ~ttem~tion. Thus, a trained diagnostician might falsely conclude that the tissue is functioning outside normal parameters, when the problem is merely the result of the ~tteMIl~tion effect.
Furthermore, by colorizing based on data from a region which may have 10 portions affected by ~ l ion and shadowing, colors may be derived that do not kuly reflect the conkrast perfusion. Without such real-time, dynamic data, it is possible that even a trained ~ gnostician might falsely conclude that the tissue is functioning in a particular m~nner, either normally or abnormally. In these methods, there lies risk for both false negative and false positive diagnoses. Real-time colorization avoids these 1 5 dangers.
EXAMPLE - Myocardial Contrast Echocardiography Referring now to Figure 3, a cut-away view of patient 30 attached to echocardiographic k~n~ cer 36 is shown. A transducer is placed on the patient, 2 0 proximate to heart muscle 32. An injection (34) of conkast agent is made into the patient's vein so that the conkast agent reaches the heart and interacts with the ulkasound waves generated by k~n~ er 36. Sound waves reflected and detected at kansducer 36 are sent as input into image processing system 38.
CA 022l7l84 l997-l0-24 W 096/33655 PCTrUS96/05834 As the contrast agent enters into various heart regions, image processing system 38 detects an increased amplitude in the reflected ultrasound waves, which is characterized by a bright~nin~ of the image. Tissue areas that do not hright~n when 5 expected may indicate a disease condition in the area (e.g. poor or no circulation, necrosis or the like).
Referring now to Figure 4, an embodiment, in block diagram form, of image processing system 38 is depicted. Image processing system 38 comprises 10 diagnostic ultrasound scanner 40, optional analog-to-digital co~lv~ l~;. 42, image processor 44, digital-to-analog converter 56, and color monitor 58. Ultrasound scanner 40 encomp~es any means of r~ tinE ultrasound waves to the region of interest and detecting the reflected waves. Scanner 40 could comprise tr~n~ cer 36 and a means of producing electrical signals in accordance with the reflected waves detected. It will be 15 appreciated that such scanners are well known in the art.
The electrical signals generated by scanner 40 could either be digital or analog. If the signals are digital, then the current embodiment could input those signals into image processor 44 directly. Otherwise, an optional A/D conv~ , 42 could be used 2 0 to convert the analog signals.
Image processor 44 takes these digital signals and processes them to provide real-time colorized video images as output. The current embodiment of image W 096/3365S PCTrUS96/0~834 processor 44 comprises a central procPc~ing unit 46, trackball 48 for user-supplied input of prel1~fin~cl regions of interest, keyboard 50, and memory 52. Memory 52 may be large enough to retain several video images and store the colorization method 54 of the present invention. CPU 44 thus colorizes video images according to stored colorization 5 method 54.
After a given video image is colorized by image processor 44, the video image is output in digital form to D/A cc,llv~lL~ 56. D/A converter thereby supplies color monitor 58 with an analog signal capable of rendering on the monitor. It will be 10 appreciated that the present invention could ~ltern~tively use a digital color monitor, in which case D/A converter 56 would be optional.
Having described a current embodiment of the present invention, the colorization method of the present invention will now be described. Figures 5-7 are 15 flowcharts describing the colorization method as ~ ly embodied. Preliminary processing begins in Figure 5 at step 62. The opc;ld~l-user selects which point in the cardiac cycle at which the series of video images will be taken. The same point in the cycle is used to reduce the amount of heart distortion from frame to frame because the heart is presumably in the same place at the same point in the cardiac cycle. Of all the 2 0 point in the cardiac cycle, the most frequently used are the end-systolic and the end-diastolic points.
W 096/33655 PCTrUS96/05834 The O1JG1~O1 then selects the region of interest to be colorized (C-ROI) in the heart at step 66. This may be accompli~hecl by allowing continuous sc~nning of the heart prior to ~lnnini.~t~.ring the contrast agent and having the operator select the C-ROI
on screen with trackball 48. Once selected, the current method allows other points on the 5 cycle to be included in the analysis at step 68.
Once all the point on the cycle and C-ROI's have been identified, the operator selects a "trigger" region of interest (T-ROI) that is used to identify that the contrast agent has or will be imminently entPrin~ entered the region of interest. For 10 ~.cses~ing myocardial perfusion, a most advantageous T-ROI would be somewhere in the heart chamber because the heart chamber receives the contrast agent prior to the muscle.
For rx;l~llillillg the left ventricle, the T-ROI may be in the right ventricle or the left atrium. Once the T-ROI is selected, the heart continues to be imaged frame-by-frame.
As each frame is acquired, the current method ~letermines whether the current frame is one of the pre-identified points of the cardiac cycle. This may be accomplished by pGlrollllil~g an electrocardiogram (ECG) on the patient at the same time that the image sequence is being captured. The ECG could then be used to supply steps 74 and 76 the data needed to ~1et~.rmine the exact point in the cardiac cycle.
If the current frame is processed at step 78, the hllellsily of each pixel is acquired in the C-ROI and the T-ROI. This hll~ y pixel data is stored and used to .
CA 022l7l84 l997-l0-24 96/33655 PCTrUS96/05834 compute an average intensity over several baseline frames. In the current method, two or three baseline frames are used and that number is tested in step 82.
At steps 84 and 86, the current method waits until there is a m~rk~l 5 change in intensity in a sufficient number of pixels in the T-ROI. This change denotes that the contrast agent has been a-lmini~tered and that the next frame is the first non-baseline frame. The first non-baseline frame is processed at step 90 in Figure 6. In step 90, for each pixel in the C-ROI, a slope and intercept of pixel intensity vs. time for the baseline frames is calculated. From this slope and h~ lsily, the baseline intensity for the 10 current frame is estim~te(l in step 92.
This method to estim~te the baseline hlL~l~ily for post-contrast frames uses the hllen,ily from pre-contrast frames. The intensity from pre-contrast frames may be simply averaged to obtain a value for baseline frames that is constant for all 15 sllc cee~ling frames. A simple average may not be sufficient in some cases to characterize the baseline as some changes in the pixel intensity may occur prior to the arrival of contrast. These changes may arise, for example, from poor image registration caused by changes in the tr~n~ cer position and/or the motion of the heart or the ROI may be adjacent to a region where contrast has arrived (e.g. the septal region of the myoc~L..li~n lying next to the right ventricle, which receives a high concentration of contrast prior to the left ventricle). In these cases, the baseline intensity is better represented by a line, which assumes that the changes will continue over time, incorporating a time dependence on the baseline intensity.
CA 022l7l84 l997-l0-24 W 096/33655 22 PCTrUS96/05834 With the b~eline hlLellsi~y calculated for each pixel, the pixel intensity is calculated by subtracting the estim~tecl baseline from the observed hl~el~ y. Once the pixel intensity has been calculated, the parameter of interest is then calculated in step 96.
5 As will be discussed below, the parameter of interest may be one of many that relate the intensity of the pixel into the time of the observed intensity. Cul~c;llLly, these parameters include time-to-arrival data, duration of hri htf-nin~, and absolute brightening For each pixel in the C-ROI, the calculated parameter is used to find the 10 particular color that the pixel receives in the current frame. The particular color may be found in a color look-up table. In this manner, a colorized image frame is produced for the first non-baseline frame in step 102. This first colorized frame produces an initial coloring for each pixel that subsequent frames may change.
S~lccee~ling frames are processed starting at step 104 in Figure 7. Again, the image sequence is tested for images that occur at the same point in the cardiac cycle at steps l 06 and l 08. If the frame is to be processed, pixel intensity is acquired, a new pixel baseline is estim~t~-l the pixel intensity is baseline subtracted, and the pararneter of interest is calculated in steps l l 0 through l l 6. At step l l 8, the current pixel intensity is 2 0 compared with the intensity in the last frame. If the current intensity value is less, then the previous color is determined in step 120. If greater, a new color is looked-up in the table. In this manner, subsequent frames are colorized and produced in step 124. Lastly, .
the current method looks for user-supplied tprrnin~tion in step 126 to complete the colorization process.
To gain a better lmt1Pr~t~n~lin~ of the application of the above-described 5 colorization method, Figures 8A-8F show a series of six frames that have been colorized using the time-to-arrival parameter. Thus, individual pixels are colored when they meet or exceed a certain hllellsily threshold at a specific time - otherwise the pixel remains uncolored. Under the current embodiment of this parameter, pixels are colored yellow if they exceed threshold within a certain time, tl; green if they have exceeded threshold 10 between time tl and another time t2; blue if threshold occurs between t2 and a later time t3; and red if threshold occurs between t3 and a later time t4.
Figures 8A-8F also depicts how the real-time colorized image processing of the present invention can make visual for the ~ gnostici~n the effects of ~ttenll~tion.
15 This particular series of real-time colorized images of exhibits both the effects of ~tt~ml~tion and a possible disease condition in the patient's heart.
Figure 8A is the first frame in the series and is taken prior to the arrival of the contrast agent; thus, no color is added to the frame. At the time of Figure 8B, time 2 0 has elapsed to somewhere between tl and t2, as defined above, because the colors yellow and green are now visible. At this time, it is clear that perfusion all around the heart muscle is occurring - even in the posterior region of the heart, since some of the posterior W O 96/33655 PCTrUS96/05834 area has been colored yellow. It should be noted that because the color yellow is fairly well distributed about the heart muscle, the effects of ~ttenll~tion are not yet present.
By the time of Figure 8C (i.e. somewhere between t2 and t3), the effects of 5 ~ttenU~tion are beginning to show. The colors blue and green are now predominant in the hemi~phere anterior to the heart chamber; whereas the posterior hemisphere is largely yellow or uncolored. Also noted in Figure 8C is a potentially ~lise~e~l region to the right of the heart chamber and in the anterior hemisphere - this region remains uncolored.
In Figure 8D, the current time is somewhere after t4, as the color red has now appeared. As the red predomin~tes in the posterior region, together with some uncolored pixels, the region is still "shadowed" by agent in the heart chamber. Both Figures 8E and 8F are likewise after time t4. By the time of Figure 8F, the vast majority of the posterior region is colorized - with red as predominant color. This coloring pattern 15 is con~i~t~nt with the expected effects of ~ ion and is made plainly visual to the diagnostician.
Additionally noted in Figures 8E and 8F, the right lateral region has been colorized red. This red colorization cannot be e~pl~ined away as due to the effects of 2 0 ~ttenll~tion. The only other plausible explanation for the late "time-to-arrival" threshold is that there is some restriction in the flow of blood to this particular region - potentially a diseased condition.
W O 96/336SS 25 PCTrUS96/05834 The images presented in Figures 8A-8F are frames that have been chosen from the real-time moving video sequence for purposes of representing the salient aspects of the invention. It can be appreciated that the present invention lies in viewing the video image as a flowing sequence of colorized frames appearing on the monitor in 5 real-time.
Other parameters are similarly depicted. Figure 9 depicts a single frame in a sequence of real-time images colorized according to the "duration of bri~htt?ning"
parameter. As noted, tbis particular color scheme uses color to denote how long a given 10 pixel was above a certain threshold. If the period of time is long, the color of the pixel is red. If the pixel was at or above the threshold for only a short period of time, the color is blue.
Figures 10 and 11 both depict a frame colorized according to the "absolute 15 bri~htening" parameter. Absolute hri3~ht~ning colors a particular pixel according to the level of intensity it has achieved. This may be accomplished by pre~1efining a set of threshold levels that are assigned dirrtlcll~ colors. If the given pixel meets a given threshold, it is assigned that particular color. The color is re~sipned only if the pixel exceeds another threshold.
It will be noted that, in some frames, the left ventricle chamber is not colorized. In some cases, it may be desirable to color the left ventricle. For example, W 096/33655 PCT~US96/05834 26 Figure 10, is an end-systolic frame without the left ventricle colored; whereas Figure 1 1 is an end-diastolic frame with the left ventricle colored.
Although only four parameters have been discussed in connection with 5 the present colorization method, it will be appreciated that more parameters that relate pixel intensity to a time element is possible and that the present invention should not be limited to the above-described parameters. Indeed, the present invention should be construed to cover any parameter that is reasonably compatible with the above-described colorization method.
There has thus been shown and described a novel method for the processing of real-time contrast enhanced, colorized images which meets the objects and advantages sought. As stated above, many changes, modifications, variations and other uses and applications of the subject invention will, however, become a~p~ ll to those 15 skilled in the art after considering this specification and accolll~ yhlg drawings which disclose pler~lled embodiments thereof. All such changes, modifications, variations and other uses and applications which do not depart from the spirit and scope of the invention are deemed to be covered by the invention which is limited only by the claims which follow.
Claims (40)
1. A method of processing grey-scale ultrasound images comprising:
a) commencement of grey scale imaging;
b) administration of contrast agent to the subject; and c) processing of images by colorization in real-time, wherein the colorization is based upon one or more parameters.
a) commencement of grey scale imaging;
b) administration of contrast agent to the subject; and c) processing of images by colorization in real-time, wherein the colorization is based upon one or more parameters.
2. The method of claim 1 wherein the contrast agent is chosen from the group consisting of liquid emulsions, solids, encapsulated fluids, encapsulated biocompatible gases and combinations thereof.
3. The method of claim 2 wherein the contrast agent employs the use of a fluorinated gas or liquid.
4. The method of claim 1 wherein the imaging is performed two-dimensionally.
5. The method of claim 1 wherein the imaging is performed three-dimensionally.
6. The method of claim 1 wherein said parameter is the time of arrival of the contrast agent.
7. The method of claim 1 wherein said parameter is the instantaneous degree of brightening of the tissue as a result of the arrival of the contrast agent.
8. The method of claim 1 wherein said parameter is the integrated degree of brightening of the tissue as the result of the arrival of the contrast agent.
9. The method of claim 1 wherein said parameter is the duration of the brightening by the contrast agent as it remains in the tissue.
10. The method of claims 1-2 and 4-9 wherein colorization pertaining to maximum values persists throughout the entire sequence.
11. The method of claim 1 wherein each pixel is independently analyzed.
12. A method of diagnosing tissue/organ condition comprising:
a) commencement of grey scale imaging;
b) administration of contrast agent to the subject, c) processing of images by colorization in real-time, wherein the colorization is based upon one or more parameters; and d) analyzing the colorized images
a) commencement of grey scale imaging;
b) administration of contrast agent to the subject, c) processing of images by colorization in real-time, wherein the colorization is based upon one or more parameters; and d) analyzing the colorized images
13. The method of claim 12 wherein contrast agent is chosen from the group consisting of liquid emulsions, solids, encapsulated fluids, encapsulated biocompatible gases and combinations thereof.
14. The method of claim 13 wherein the contrast agent employs the use of a fluorinated gas or liquid.
15. The method of claim 12 wherein the imaging is performed two-dimensionally.
16. The method of claim 12 wherein the imaging is performed three-dimensionally.
17. The method of claim 12 wherein said parameter is the time of arrival of the contrast agent.
18. The method of claim 12 wherein said parameter is the instantaneous degree of brightening of the tissue as a result of the arrival of the contrast agent.
19. The method of claim 12 wherein said parameter is the integrated degree of brightening of the tissue as the result of the arrival of the contrast agent.
20. The method of claim 12 wherein said parameter is the duration of the brightening by the contrast agent as it remains in the tissue.
21. The method of claim 12 wherein the diagnosis pertains to the heart.
22. The method of claim 21 wherein the processing is performed in parallel at more than one point in the cardiac cycle.
23. The method of claims 21 or 22 wherein the colorization includes the left ventricle region.
24. The method of claims 21 or 22 wherein the colorization does not include the left ventricle region.
25. The method of claim 12 wherein the diagnosis pertains to the kidney.
26. The method of claim 12 wherein the diagnosis pertains to the brain.
27. The method of claim 12 wherein the diagnosis pertains to the liver.
28. The method of claim 12 wherein the diagnosis pertains to the testes.
29. The method of claim 12 wherein the diagnosis pertains to muscle tissue.
30. The method of claim 12 wherein the diagnosis pertains to the blood flow within tissue/organ.
31. The method of claim 12 wherein the processing is performed in parallel at more than one point in the cardiac cycle.
32. The method of claim 12 wherein each pixel is independently analyzed.
33. A method for producing real-time colorized images in an ultrasound diagnostic scanning apparatus or an ultrasound image processing apparatus wherein the apparatus processes a series of grey scale images according to a pre-determined parameter; the steps of the method comprise:
(a) identifying regions of interest in the images for processing;
(b) for each grey scale image requiring processing, (i) determining the value of the parameter of choice for a frame, (ii) comparing the value in (i) to the value for the previous frame, (iii) colorizing the regions of interest based upon the values in (ii).
(a) identifying regions of interest in the images for processing;
(b) for each grey scale image requiring processing, (i) determining the value of the parameter of choice for a frame, (ii) comparing the value in (i) to the value for the previous frame, (iii) colorizing the regions of interest based upon the values in (ii).
34. The method of claim 33 wherein the apparatus is for two-dimensional imaging;
35. The method of claim 33 wherein the apparatus is for three-dimensional imaging.
36. The method of claim 33 wherein the parameter of choice is the time of arrival of contrast agent.
37. The method of claim 33 wherein the parameter of choice is the instantaneous degree of brightening of the tissue as a result of the arrival of contrast agent.
38. The method of claim 33 wherein the parameter of choice is the integrated degree of brightening of the tissue as the result of the arrival of contrast agent.
39. The method of claim 33 wherein the parameter of choice is the duration of brightening by the contrast agent as it remains in tissue.
40. The method of claim 33 wherein the step (a) further comprises:
(a)(i) identifying a point or points in the cardiac cycle at which the series of grey scale images are selected for further processing.
(a)(i) identifying a point or points in the cardiac cycle at which the series of grey scale images are selected for further processing.
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| US4572203A (en) * | 1983-01-27 | 1986-02-25 | Feinstein Steven B | Contact agents for ultrasonic imaging |
| JPS62122635A (en) * | 1985-11-22 | 1987-06-03 | 株式会社東芝 | Radiation image treatment apparatus |
| US5425366A (en) * | 1988-02-05 | 1995-06-20 | Schering Aktiengesellschaft | Ultrasonic contrast agents for color Doppler imaging |
| GB2219905A (en) * | 1988-06-17 | 1989-12-20 | Philips Electronic Associated | Target detection system |
| EP0533782B1 (en) * | 1990-06-12 | 1999-11-24 | University Of Florida | Automated method for digital image quantitation |
| US5457754A (en) * | 1990-08-02 | 1995-10-10 | University Of Cincinnati | Method for automatic contour extraction of a cardiac image |
| US5239591A (en) * | 1991-07-03 | 1993-08-24 | U.S. Philips Corp. | Contour extraction in multi-phase, multi-slice cardiac mri studies by propagation of seed contours between images |
| US5255683A (en) * | 1991-12-30 | 1993-10-26 | Sound Science Limited Partnership | Methods of and systems for examining tissue perfusion using ultrasonic contrast agents |
| US5235984A (en) * | 1992-03-30 | 1993-08-17 | Hewlett-Packard Company | On-line acoustic densitometry tool for use with an ultrasonic imaging system |
| US5469849A (en) * | 1993-06-14 | 1995-11-28 | Kabushiki Kaisha Toshiba | Ultrasound diagnosis apparatus |
| JP3403809B2 (en) * | 1993-06-14 | 2003-05-06 | 株式会社東芝 | Ultrasound diagnostic equipment |
| NO943269D0 (en) * | 1994-09-02 | 1994-09-02 | Vingmed Sound As | Method for analyzing and measuring ultrasound signals |
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| US5743266A (en) | 1998-04-28 |
| JPH11504242A (en) | 1999-04-20 |
| AU5578196A (en) | 1996-11-18 |
| EP0822780A1 (en) | 1998-02-11 |
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