CN100543774C - Be used for the system and method that colon wall extracts - Google Patents
Be used for the system and method that colon wall extracts Download PDFInfo
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- CN100543774C CN100543774C CNB2005800364350A CN200580036435A CN100543774C CN 100543774 C CN100543774 C CN 100543774C CN B2005800364350 A CNB2005800364350 A CN B2005800364350A CN 200580036435 A CN200580036435 A CN 200580036435A CN 100543774 C CN100543774 C CN 100543774C
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Abstract
A kind of system and method that colon wall extracts that is used for is provided.Described method comprises: place seed (520) in the image of patients abdomen; Determine the feature (530) of the adjacent volume elements of described seed and described seed; And, use the sorter of being trained to distinguish described colon wall and near the region growing (540) of object to finish colon wall according to the feature of the adjacent volume elements of described seed and described seed.
Description
The cross reference of related application
The application requires the U.S. Provisional Application NO.60/604 of 24 submissions August in 2004,106 right, and its copy is quoted by reference at this.
Technical field
The present invention relates to medical image analysis, relate in particular to the system and method that under the situation that has tagged fecal matter or folding colon regions, is used for the colon wall extraction.
Background technology
Present colon cancer is in the world classified the second main cause of cancer mortality as.Most of colorectum cancers are produced by the adenoma polyp at first.The early stage inspection and the excision that studies show that polyp of colon can reduce the risk of suffering from colon cancer, thereby reduce mortality ratio.Unfortunately, the conventional method that is used to check polyp of colon be get involved, uncomfortable and complication arranged.
Computed tomography (CT) colon figure or virtual colon inspection technique have become the screening technique of a kind of potential replacement of polyp of colon and block.It combines the belly Spiral CT scan according to the non-intervention evaluation of mucous membrane of colon with visualization tool.But it is time-consuming that the inspection of virtual colon inspection technique is judged, and the accuracy of polyp inspection depends on employed display technique and doctor's level professional technology.
Recently, computer-aided diagnosis and inspection (CAD) system that developed is used for self-verifying polyp and block, and the position of colon suspicious region is provided.As shown in Figure 1, this CAD system algorithm attempting to have considered transition between colon wall 110 and the air 120 (as: black region) is used for the polyp inspection.And as shown in Figure 2, when in the colon 200 excreta or ight soil 250 being arranged, owing to do not have the transition of colon wall 210 to air 220 in the zone that described excreta 250 covers, therefore described algorithm must be removed these excretas 250.
But, remove the artefact that excreta will cause described colon wall appearance and characteristic changing, and will influence follow-up polyp analysis and inspection that observer and CAD algorithm are done.Therefore, need a kind of technology to compensate and have excremental situation in the colon, its existence can not influence conversely to the wherein analysis and the inspection of polyp like this.
And when having folding colon regions, it is discontinuous that in fact the part colon becomes, and be difficult to follow the tracks of described colon wall or its center line in the described fold domain.Therefore, need a kind of technology folding to analyze colon wall when regional existing, this technology has improved the sensitivity of existing CAD algorithm, and has improved that virtual colon inspection technique " is passed through " and the quality of center line extractive technique.
Summary of the invention
The present invention with diagnosis and the inspection that aids in the colon relevant disease, solves the above-mentioned and other problem that runs in the prior art by a kind of system and method that colon wall extracts that is used for is provided under the situation that has tagged fecal matter or folding colon regions.
In one embodiment of the invention, a kind of method that is used for extracting colon wall comprises: the image at colon is placed seed; Determine the feature of the adjacent volume elements of seed voxel and these seeds; And according to the feature of the adjacent volume elements of described seed and these seeds, with being distinguished described colon wall and near object by the sorter of being trained finishing a kind of region growing of described colon wall, wherein said feature comprises minimum value, maximal value or the square of distance feature of the adjacent volume elements of brightness, shape, texture or described seed and these seeds.
Described seed is placed as follows: in the air on a colon wall, in the colon wall, near the fat the colon wall, in the excreta in the colon wall or in the fold domain of colon wall.These seeds automatically or the artificially place.Wherein a kind of acquisition of the imagery exploitation CT of patients abdomen or magnetic resonance (MR) imaging technique.
Described be characterized as one of following: the distance feature of the adjacent volume elements of the statistical property of brightness, shape, texture or described seed and these seeds.Described statistical property is one of following: minimum value, maximal value or square.Object is one of following near described: excreta, air, muscle, fat or liquid.
Described method also comprises: the view data that obtains patient; From described view data, select the sample volume elements; Determine the feature of the adjacent volume elements of described sample volume elements and these sample volume elements; Training classifier is to distinguish described colon wall and near object; And verify described sorter.Described method comprises that also the described region growing of restriction leaks into adjacent areas.
In another embodiment of the present invention, a kind of method that is used for following the tracks of colon wall comprises: the abdomen images patient is placed a plurality of seed voxel; Determine the feature of these seed voxel and adjacent volume elements thereof, wherein said be characterized as one of following: the distance feature of the statistical property of brightness, shape, texture or described seed voxel and adjacent volume elements thereof; And according to these features, distinguish described colon wall and near object to finish the region growing of colon wall by using the sorter of being trained, thereby determine the continuity of described colon wall, wherein said statistical property is one of following: minimum value, maximal value or square.
Described statistical property is one of following: minimum value, maximal value or square.Object is one of following near described: excreta, air, muscle, fat or liquid.
Also have in another embodiment of the present invention, a kind of system that is used for extracting colon wall comprises: the device of placing seed at the image of patients abdomen; Determine the device of feature of the adjacent volume elements of described seed and described seed; And according to the feature of the adjacent volume elements of described seed and these seeds, with being distinguished described colon wall and near the object device with the region growing of finishing colon wall by the sorter of being trained, wherein said feature comprises minimum value, maximal value or the square of distance feature of the adjacent volume elements of brightness, shape, texture or described seed and these seeds.
Described seed is placed as follows: in the air on a colon wall, in this colon wall, near the fat this colon wall, in the excreta of colon wall or in the fold domain.Described be characterized as one of following: the distance of the adjacent volume elements of the statistical property of brightness, shape, texture or described seed and these seeds.Described statistical property is one of following: minimum value, maximal value or square.Object is one of following near described: excreta, air, muscle, fat or liquid.
Described processor also operate with described program code so that: the view data that obtains patient; From described view data, select the sample volume elements; Determine the feature of the adjacent volume elements of described sample volume elements and these sample volume elements; Training classifier is to distinguish described colon wall and near object; And verify described sorter.Described processor is also operated to limit described region growing with described program code and is leaked.Wherein a kind of acquisition of the imagery exploitation CT of described patients abdomen or magnetic resonance (MR) imaging device.
Also have in another embodiment of the present invention, a kind of method that is used for determining the colon polyp locations is provided.This method comprises: place seed in the image of colon; Determine the feature of the adjacent volume elements of described seed and described seed; According to the feature of the adjacent volume elements of described seed and described seed, distinguish described colon wall and near object finishing the region growing of colon wall by using the sorter of being trained, thereby extract a wall of described colon; And determine the position of polyp on this colon wall with the colon wall of described extraction.
Above-mentioned feature is to represent embodiment's and be suggested to help to understand the present invention.Should be appreciated that they do not attempt to be considered to described claim is limit the restriction of the present invention of justice, or to the equivalence restriction of claim.Therefore, the general introduction of this feature should not be considered to definite equivalence.In the following description, will become cheer and bright with claim further feature of the present invention with reference to the accompanying drawings.
Description of drawings
Fig. 1 is not for there being excremental colon image;
Fig. 2 is underlined excremental colon image;
Fig. 3 is a kind of system chart that is used to extract colon wall according to one exemplary embodiment of the present invention;
Fig. 4 is a process flow diagram, shows a kind of training classifier that is used for according to one exemplary embodiment of the present invention to distinguish the method for described colon wall and near object;
Fig. 5 is a process flow diagram, shows a kind of method that is used to extract colon wall according to one exemplary embodiment of the present invention; And
Fig. 6 is the colon image that inconsistent tagged fecal matter is arranged.
Embodiment
Fig. 3 is according to one exemplary embodiment of the present invention, is used for the block diagram of the system 300 of colon wall extraction under the situation that has tagged fecal matter or folding colon regions.As shown in Figure 3, described system 300 comprises scanister 305 therein, personal computer (PC) 310, with the operator's console 315 that links to each other such as Ethernet 320.Described scanister 305 can be MR imaging device, CT imaging device, spiral CT imaging device or can CT, MR, the mixing imaging device of positron emission x-ray tomography (PET) or other imaging technique.
Described PC 310 can be portable or laptop computer, workstation or the like, and it comprises: CPU (central processing unit) (CPU) 325 and storer 330, this storer are with input 350 and export 355 and link to each other.Described CPU 325 comprises extraction module 345, and this module comprises one or more methods that is used for extracting colon wall under the situation that has tagged fecal matter or folding colon regions.
Described storer 330 comprises random-access memory (ram) 335 and ROM (read-only memory) (ROM) 340.Described storer 330 also can comprise: database, disc driver, tape drive or the like, or its combination.Described RAM 335 plays data-carrier store, employed data and be used as the workspace term of execution that it being stored in the program of described CPU 325.Described ROM 340 plays the program storer, is used for storing the program that described CPU 325 carries out.Described input 350 is made of keyboard, mouse etc., and described output 355 is by LCD (LCD), cathode ray tube (CRT) display, or printer constitutes.
The operation of described system 300 is controlled from operator's console 315, and this control desk comprises controller 365, as: keyboard, and display, as: CRT monitor.Operator's console 315 communicates with described PC 310 and described scanister 305, like this, two dimension (2D) view data of being collected by described scanister 305 just can be drawn into three-dimensional (3D) data by described PC 310, and observed on described display 360.Be to be understood that, described PC 310 can be set under the situation that lacks described operator's console 315, operation and show the information that described scanister 305 is provided, for example, utilize described input 350 and output 355 devices to carry out the particular task of carrying out by described controller 365 and display 360.
Described operator's console 315 can also comprise any suitable image drawing system/tool/application, it can handle the Digital Image Data of the image data set (or its part) that is obtained, so that generate on described display 360 and demonstration 2D and/or 3D rendering.Especially, described image drawing system can be that a kind of 2D/3D that medical image is provided draws and visual application, and this is applied on general purpose or the specific computer workstation and carries out.And described image drawing system can make the user navigate by 3D rendering or a plurality of 2D image slices.Described PC310 can also comprise an image drawing system/tool/application, is used to handle the Digital Image Data of the image data set that is obtained, to generate and demonstration 2D and/or 3D rendering
As shown in Figure 3, described extraction module 345 can also be used for receiving and handling digital medical image data by described PC310, as mentioned above, these data can be raw image data, 2D data reconstruction (as: axially tomography), or such as the form of the 3D data reconstruction of volumetric image data or complex plane reformatting (multiplanar reformata), or any combination of these forms.Described data processed result can be exported to image drawing system in the described operator's console 315 through described network 320 by described PC310, be used for according to fragment such as organ or anatomical structure, the described data processed result of color or brightness variation etc., the 2D and/or the 3D that produce view data draw.
Fig. 4 shows a kind of training classifier that is used for to distinguish the method for described colon wall and near object.As shown in Figure 4, the one or more abdomen scannings from one or more patients obtain view data (410).By using described scanister 305, be CT scanner in this example, this device is by described operator's console 315 operations, and the belly that scans patient is to produce a series of 2D image slices relevant with colon.Then these 2D image slices are made up to constitute a 3D rendering.
After obtaining described CT view data, the data sample (420) of near fat selected marker and unmarked excreta or ight soil, the described colon wall or muscle, described colon wall itself, the colon regions that folds, air, water or contrast material.Next, calculate those zones (as: neighborhood) around independent sample point volume elements and described each volume elements such as features such as statistical property (430).For example, the described statistical property that is calculated to be brightness minimum value, maximal value or square (as: standard deviation, deflection and kurtosis).The size that should be appreciated that neighborhood can change, and can determine according to some factors such as the colon wall thickness of being sampled, folding colon regions, air, ight soil, fat or muscle.Characterize shape, texture, distance, and the further feature of the statistical property of the local neighborhood of different sizes can calculate in step 430 around the sample point.Diversified feature selecting algorithm is arranged,, all can be used to select correlated characteristic and the neighborhood size that in follow-up sorter training technique, to use as greedy (greedy) search or genetic algorithm.
Utilize the feature calculate and the statistical property of described sample point and local neighborhood thereof then, train a sorter or a plurality of sorter distinguishing described colon wall and near object, as: as described in fat, muscle, air, ight soil or the liquid (440) of colon inboard.Should be appreciated that half supervision in many or single classification of type that can use supervision fully in this step, non-supervision sorter training technique.As soon as finish the training of a described sorter or a plurality of sorters distinguishing described colon wall and near object, a kind of checking carried out, as: leaving-one method or N folding cross validation technology, and a checking (450) of relevant a certain independent separate test set.
Fig. 5 is a process flow diagram, shows a kind of method of operating that is used for extracting colon wall under the situation that has tagged fecal matter or folding colon regions according to one exemplary embodiment of the present invention.As shown in Figure 5, for example, from certain patient's abdominal CT scan acquisition view data (510).This just can finish by using with reference to the described same or analogous technology of above step 410.
When after described colon obtains the CT view data, just in this colon or the one or more seeds of placed around (520).For example, described seed can be placed in the described colon wall 210, or in the pressure dome 220 of colon 200 inboards, as shown in Figure 2.In addition, described seed can be placed in fat 240 or the muscle 230, in described excreta 250 or in folding colon regions.Can make described excreta 250 or ight soil be special color to come the described excreta 250 of mark by allowing patient swallow oral contrast reagent such as barium or iodine.
Should be appreciated that in step 520, can by use determine pressure dome in colon the position or certain algorithm of the position of ight soil in colon place described seed automatically, and locate described colon wall.Described seed can also manually be placed.For example, the user can click in the colon or on every side a certain required seed points with cursor of mouse simply.
In case placed described seed, just calculate and characterize shape, texture, distance, and the features such as statistical property (530) of described seed and local neighborhood.This finishes by using with reference to the described same or analogous technology of above step 430.The described sorter that to train in step 440 then or a plurality of sorter together are applied to a region growing (540) of described colon wall 210.Especially, use the output of described sorter of being trained or a plurality of sorters, and to the region growing finishing described colon wall 210 with approximate measure that approaches of all volume elements.According to the described region growing of finishing, determine the continuity of described colon wall 210, therefore, just can extract, follow the trail of or follow the tracks of described colon wall 210.Should be appreciated that except in step 540, in the process of described region growing, using a described sorter or a plurality of sorter, can also use other similar measurements.
For the further continuity of the colon wall of reinforced region growth, and be used for analyzing for medical professional or polyp detection algorithm provide clearer and do not have artifactitious described colon wall image, can on the colon wall of described region growing, carry out one group of post-processing step (550).Such process comprises that the described region growing of restriction leaks into the unmarked part 640 of excreta 630, does not have contrast agent 620 therein.Its example is shown in the colon image 600 of Fig. 6.For example, use morphological operations, remove by those volume elements that will have the neighborhood that is less than predetermined quantity, or, can prevent that just region growing from leaking into the unmarked part 640 of excreta 630 by little separation group is removed.And, though should pay close attention to muscle shown in Figure 1 130 or fat 140 those zones near described colon wall 110, but the fragment that leaks into described muscle 130 can not influence the quality in described colon wall 110 medial region growth, and this all is important for clinician, surface and Volume Rendering Techniques and polyp detection algorithm as a rule.
According to one exemplary embodiment of the present invention, when excreta that has mark or part mark or folding colon regions, colon wall can extract by thin muscle layer.Like this, making the inside of described colon wall can all be visual " the passing through " during virtual colon is checked, be used to the position local endoscope of polyp thereon and check, or in conjunction with a kind of expansion or the replacement of checking technology as artificial or robot brain auxiliary diagnosis and polyp.
Should also be understood that because some in described composition system element of accompanying drawing and the method step can realize with software, so the mode that is programmed according to the present invention, the actual connection between described system element (or treatment step) can be different.Provided these guidances provided by the invention, those skilled in the art can imagine these and similar realization or configuration of the present invention.
Should also be understood that above description only is representational exemplary embodiment.The reader more than describes on the representational sample that concentrates on possibility embodiment, on the sample of the exemplary illustration principle of the invention for convenience.These are described not attempt not have and enumerate all possible modification with omitting.Those alternative embodiments that may not show specific part of the present invention, or those available replacement parts of not describing should not regarded the abstention of those alternative embodiments as.Other is used and embodiment can not realize in breaking away from the spirit and scope of the present invention.
Because therefore above-mentioned a large amount of exchanges and combination and comprise the realization that non-invention substitutes and all can be established above-mentioned, do not attempt the present invention is limited on those embodiment of specific description, but the present invention is defined according to following claim.Be appreciated that many embodiment that do not describe all in the literal scope of following claim, and other be equivalent.
Claims (17)
1. method that is used to extract colon wall comprises:
In the image of patients abdomen, place seed;
Determine the feature of the adjacent volume elements of described seed and described seed; And
Feature according to the adjacent volume elements of described seed and these seeds, with being distinguished described colon wall and near object by the sorter of being trained finishing the region growing of colon wall, wherein said feature comprises minimum value, maximal value or the square of distance feature of the adjacent volume elements of brightness, shape, texture or described seed and these seeds.
2. the process of claim 1 wherein that described seed is placed on the colon wall, in the air in the colon wall, near the fat the colon wall, in the excreta in the colon wall or in the fold domain of colon wall.
3. the method for claim 2, wherein said seed automatically or the artificially place.
4. the method for claim 2, wherein said excreta is labeled.
5. the process of claim 1 wherein that the imagery exploitation CT or the MR imaging technique of described patients abdomen obtain.
6. the process of claim 1 wherein described near object be one of following: excreta, air, muscle, fat or liquid.
7. the method for claim 1 also comprises:
Obtain the view data of patients abdomen scanning;
From described view data, select the sample volume elements;
Determine the feature of the adjacent volume elements of described sample volume elements and these sample volume elements;
Training classifier is to distinguish described colon wall and near object; And
Verify described sorter.
8. the method for claim 1 also comprises: determine the position of polyp on described colon wall with the colon wall of described extraction.
9. the method for claim 1 also comprises:
Limiting described region growing leaks.
10. method that is used to follow the tracks of colon wall comprises:
In colon image, place a plurality of seed voxel;
Determine the feature of described seed voxel and adjacent volume elements thereof, wherein said be characterized as one of following: the distance feature of the statistical property of brightness, shape, texture or described seed voxel and adjacent volume elements thereof; And
According to described feature, distinguish described colon wall and near object finishing the region growing of colon wall by using the sorter of being trained, wherein said statistical property is one of following: minimum value, maximal value or square.
11. the method for claim 10, wherein said near object be one of following: excreta, air, muscle, fat or liquid.
12. a system that is used to extract colon wall comprises:
In the image of patients abdomen, place the device of seed;
Determine the device of feature of the adjacent volume elements of described seed and described seed; And
Feature according to the adjacent volume elements of described seed and these seeds, with being distinguished described colon wall and near the object device with the region growing of finishing colon wall by the sorter of being trained, wherein said feature comprises minimum value, maximal value or the square of distance feature of the adjacent volume elements of brightness, shape, texture or described seed and these seeds.
13. the system of claim 12 is near the fat in the air that wherein said seed is placed on the colon wall, this colon wall is interior, this colon wall, in the excreta or in the fold domain of colon wall.
14. the system of claim 12, wherein said near object be one of following: excreta, air, muscle, fat or liquid.
15. the system of claim 12 also comprises:
Obtain the device of the view data of patients abdomen;
From described view data, select the device of sample volume elements;
Determine the device of feature of the adjacent volume elements of described sample volume elements and described sample volume elements;
Training classifier is to distinguish the device of described colon wall and near object; And
Verify the device of described sorter.
16. the system of claim 12 also comprises:
Limit the device that described region growing leaks.
17. the system of claim 12, wherein a kind of acquisition of the imagery exploitation CT of wherein said patients abdomen or magnetic resonance imagine device.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US60410604P | 2004-08-24 | 2004-08-24 | |
| US60/604,106 | 2004-08-24 | ||
| US11/176,533 | 2005-07-07 |
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| Publication Number | Publication Date |
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| CN101048797A CN101048797A (en) | 2007-10-03 |
| CN100543774C true CN100543774C (en) | 2009-09-23 |
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Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101766491B (en) * | 2010-02-04 | 2013-02-27 | 华祖光 | Method and system for virtual colonoscopy without making preparation of cleaning intestinal tract |
| CN108009567B (en) * | 2017-11-10 | 2021-11-02 | 电子科技大学 | Automatic excrement character distinguishing method combining image color and HOG and SVM |
| CN108596237B (en) * | 2018-04-19 | 2019-11-15 | 北京邮电大学 | A kind of endoscopic polyp of colon sorter of LCI laser based on color and blood vessel |
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2005
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Non-Patent Citations (2)
| Title |
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| Closed boundary extraction of large intestinal lumen. KRISHNAN S M ET AL.ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY,1994.ENGINEERING ADVANCES:NEW OPPORTUNITIES FOR BIOMEDICAL ENGINEERS.,PROCEEDINGS OF THE 16TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE BALTIMORE. 1994 |
| Closed boundary extraction of large intestinal lumen. KRISHNAN S M ET AL.ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY,1994.ENGINEERING ADVANCES:NEW OPPORTUNITIES FOR BIOMEDICAL ENGINEERS.,PROCEEDINGS OF THE 16TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE BALTIMORE. 1994 * |
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