CN1031811C - 基于神经网络的自动细胞试样分类系统和方法 - Google Patents

基于神经网络的自动细胞试样分类系统和方法 Download PDF

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CN1031811C
CN1031811C CN89102194A CN89102194A CN1031811C CN 1031811 C CN1031811 C CN 1031811C CN 89102194 A CN89102194 A CN 89102194A CN 89102194 A CN89102194 A CN 89102194A CN 1031811 C CN1031811 C CN 1031811C
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马克·R·鲁滕贝格
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Abstract

一对细胞试样进行分类的自动筛选系统，其中的分类使用了神经网络，该系统还包括自动显微镜和有关的图像处理电路。

Description

基于神经网络的自动细胞试样分类系统和方法
本发明总的涉及，如标题所指的那样细胞分类，更具体地说涉及利用神经网络和/或神经计数机以提高细胞分类速度和精确度。
子宫颈部涂片(巴氏试验)是唯一大量筛选的细胞学检查，这种检查要求用肉眼检查在载片上的每一个细胞。由于目前的手工操作所固有的单调和疲劳，使得这种试验存在着很高的错误率。细胞分类一般是按“计件工作”来执行的，这种计件工作是由病理实验室雇用的和有些地方由按月付薪水的细胞学专家来进行的。由于高错误率有可能导致诊断不出子宫颈癌从而带来威胁生命后果。所以，美国癌症协会正在考虑把所建议巴氏涂片检查频率提高二倍。但是，这样势必使得已经超载的子宫颈癌普查业更加超载，因为越来越多人不愿意从事这种单调而紧张的手工子宫颈部涂片分类工作。美国癌症协会关于增加巴氏涂片频率的建议的结果只能是增加了错误率，因为增加巴氏涂片频率势必减少花在每张涂片上的手工检验的时间。每张涂片的详尽的手工检验至少要化费15分钟，而一个细胞学技术专家，龙其是在满负荷工作条件下，所花费的时间可能不到一半。美国病理研究院充分了解了这一问题并且将谋求用自动化来解决子宫颈涂片筛选问题手段。
由于自动子宫颈涂片分析方法有明显的市场前景，在已有技术中已有好几种尝试，这种尝试均告失败，因为它们仅仅依赖于传统的图形识别技术(几何图形，符号关系学，样板，统计技术)或基于人工智能(AI)的图形识别，即基于规则的专家系统。但是，目前并没有明显的算法或完整、明显细胞学技术专家或病理学家利用他们的经验综合大量特征以格式塔(gestalt)方式进行分类的规则。因此，子宫颈涂片分类对于基于神经网络的图像识别来说是一个极好的应用。已有技术存在的局限性的例子可以在1987年的Tien等人的题为“自动子宫颈筛选分类”一文中看到。
有关的背景材料如下：
鲁姆哈特(Rumelhart)，德维德(David).E，和姆科勒伦达(Moclelland)杰姆斯(James).L，“平行分布处理”，MIT出版社1986，第一卷。
廷(Tien)，D.等，“自动颈部涂片分类”，电气与电子工程师协会/医学和生物学工程第九次年会会刊。1987，1457—1458页。
赫克特—尼尔森，罗伯特(Hecht—Nielsen，Robert)，“神经计算：模仿人脑”，电气与电子工程师协会谱，1988.3，36—41页；和
李普曼(Lippman)，理查得(Richard)P，“关于神经网络计算初探”，电气与电子工程师协会ASSP杂志1987.4，4-22页。
因此，本发明的主要目的在于提供一个关于把细胞试样分门别类的自动系统和方法，例如，显著特征的分门别类。
简单地说，本发明包括一初级分类器(有时称作一级分类器)以初步地将细胞试样分类和一次级分类器(有时称作二级分类器)以把初级分类器挑选出来的细胞试样的部分进行分类以供以后进一步的分类，其中，该次级分类器包括一神经计算或神经网络。
在一实施例中，一级分类器可以包括市场上可以购得的以标准显微镜形式出售的自动显微镜，这种显微镜带有摄像机或电荷耦合器件阵列，显微镜载片可加以控制以自动扫描载片。从摄像机中所得到的图像被数字化和输出到以计算系统存在的二级分类器中。该计算机系统包括一个下面将详细说明的神经网络，这种神经网络在这里援引的几个参考材料中也有所揭示。包括神经网络的计算系统用来识别细胞图像并把它们按有关诊断特征分成若干类别。在另一实施例中，该初级分类器可以包括一神经网络。下面还揭示了其他一些实施例。
本发明的进一步目的在于在手工仔细筛透完成这项工作所花费的时间内执行对试样的分类工作。即：约15分钟/试样。
本发明的进一步目的在于对细胞试样进行的分类，还包括有关目的物的数目及类型，而不单是对在子宫涂片中可以找到的一般的单层细胞(例：细胞群，重叠细胞，碎片，白血球，细菌，粘液)。
本发明的进一步目的在于在进行上面描述的子宫颈涂片的分类时能探测前期恶性细胞和恶性细胞。
本发明的进一步目的在于能以比传统的手工子宫颈涂片筛选错误率为小的错误率进行。
本发明的细胞分类系统的一个优点在于它将细胞试样按医学显著特征的分类将更为可靠，即具有较小的差错率。
本发明的细胞分类系统的一个进一步的优点在于它不需要在对从病人处得到细胞的试样的步骤上再作进一步的改变。
本发明的细胞分类系统的一个进一步优点在于它将在允许经济地进行手术的操作时间限制内允许可靠的分类。
对那些在该技术领域内的具有普通技能的人来说，在阅读了下面所提到的实施例的详细说明后，本发明的种种目的，优点和特征将变得非常明显。
这里所引用的已出版的文章在这里专供参考之用。
此外，本发明在这里主要是针对以子宫颈涂片形式的细胞试样分类，即巴氏试验中所用的方式进行描述的。但是应当知道这是本发明原理运用的一个例子，本发明也可以用于许多其他细胞试样的分类。
在附图中：
图1是根据本发明的基于神经网络的自动细胞试样筛选装置的示意性方框图；
图2是实施例中所用的三层神经网络的示意图。
图3是根据本发明的自动筛选装置的另一实施例的方框图。
图4是根据本发明的自动筛选装置的又一个实施例的方框图。
图5是根据本发明的自动筛选装置的再一个实施例的方框图。
图6是根据本发明的自动筛选装置的又一个实施例的方框图，以及
图7是根据本发明的自动筛选装置的再一个实施例的方框图。
图1是根据本发明的基于神经网络的自动细胞试样筛选装置的示意图，图中该装置总的用码号10表示。该分类装置10包括一自动显微镜11，一摄像机或CCD元件12，一图像数字转换器13，和分类级14，15和17。
该自动显微镜11使显微镜物镜和试样产生相对移动，而摄像机或CCD12得到一细胞试样的特定部分的图像或照片。该图像经图像数字转换器13加以数字化，从中得到的信息送到分类器14上。在所述的实施例中，分类器14是市场上可以买到的通过测量它们的总的光密度(核染色密度)而鉴定有关的细胞核的统计分类器。这是对光学误差进行校正过的物体象素灰值的总和。与正常细胞相比，恶性细胞趋向于具有一个较大而浓的染色的核。
经过分类器14的物体包括前期恶性细胞和恶性细胞，但同时还包括其它诸如细胞群、鳞片、白血球和粘液等具有高度总光密度的物体。二级分类器15的任务就是将前期恶性细胞和恶性细胞与这些其他物体区分开来。
在二级分类器15中采用了神经网络，适于二级分类器15的神经网络的设计和操作详细说明可以在这里引用的参考文献中找到。下面提供这种信息的简单的说明。
以细胞试样初级分类器中得到的数据为基础，该二级分类器被用于检验，例如，决定需要进一步筛选或分类的该试样的特定的区域。二级分类器的这种进一步的检验可以根据已经取得的试样中被挑选出来的区域的数字化的图像数据来进行，或者根据由元件11-13或其他市场上可以买到的可以为二级分类器15的使用和分析提供可接受的数据的光学的或其他的仪器所得到的数据进行。
神经网络是一个具有定向图表布局的高度平行分布系统，神经网络上的节点通称为“处理元件”或“神经层”，而其间的链接通称为“内连”，每一个处理元件接受多种输入而产生一单一的输出信号，它分成多个拷贝，然后这些拷贝再分布给其他处理元件作为输入信号。信息按称为“权重”的链接强度存储存储起来。每一个处理元件用不同步的方式计算着每一输入线上的权重乘以该线上信号电平(通常为0或1)的乘积之和。如果乘积之和超过预置活性阈值，处理元件的输出便置位于1，如果小于它，便置位于0。通过权重值的调节实现学习。
对于本发明来说，所述的实施例用在李普曼(LIPPMAN)的参考文献中所描述的三层神经网络作为感知器。在鲁梅哈特(Rumelhart参考文献第8章对三层神经网络有详细的叙述。其他类型的神经网络系统也可使用。
三层神经网络包括一输入层，一输出层，和一隐藏着的中间层。该中间层用以供网络内部图形的表示用。如明斯基(Minsky)和帕佩尔特(Papert)在他们1969的题为“感知器”的书中所指示的那样，两层相关的网络所能解决的问题的类型是有限的，只具有“输入”和“输出”处理元元件的两层网络只能表示相似的输入图形导致相似的输出图形的映射。当实际的问题不是这种类型时，就需要三层网络。业已证实具有一足够大的隐藏层的三层神经网络总可以找到一个可以将一个输入图形映射成所要求的输出图形的表示方法。用在所述的实施例采用的这种三层神经网络示于图2中。
神经网络结构的几个重要的特点使它们与已有技术中用于分类器15的方法有所不同。
1.很少或没有执行功能。只有极为简单的各自进行其乘积之和计算的单元。每一处理元件的任务限于从其相邻处接受输入并且，作为这些输入的一个函数，计算出送往其相邻处的输出值。每一个处理元件周期性地，与其任何相邻(元件)的活动平行，但不同步地执行着这种运算。
2.所有的知识信息都存在于联结处。只有很短暂的存储可以发生在处理元件的状态上。所有长存储是通过在处理元件之间的连接的“强度”或“权重”值加以表现的。正是建立这些权重以及改变它们以进行学习的规则使神经网络模型彼此区别。所有的知识信息隐函地表示在权重连接的强度中，而不是明显地表示在处理元件的状态中。
3.与算法计算机和专家系统不同，神经网络学习的目的并不是形成算式或一套明显的规则。一个神经网络在学习过程中自我组织以建立一整套权重。这一整套权重将产生出对一给定输入来说最接近于它被先知是该输入的正确输出的输出。正是这种连接强度的适应性获得允许神经网络具有好象它了解规则的行为。一般的计算机用在信息可以明显地以算法或明显且完整地以一套规则表示的场合是非常好的。如果不是这种情形时，一般的计算机就会遭到很大的困难。虽然一般的计算机进行算法运算时运比任何人都快，它们在执行非算法运算的任务中例如在图像识别，最近邻的分类，和面对许多同时联立的约束要求达到最佳答案时就很难与人类相匹敌。如果要寻找N样品图形以分类出一未知的输入图形，如果一算法系统可以在约N时间内完成这项任务。在一神经网络中，所有的供选择物的特征同时通过整个系统中的一整套连接权重表示出来。所以神经网络在自动地以1时间到达模糊输入的最邻近值而不是N时间。
对本发明的来说，所述的实施例是通过用如鲁姆哈特(Rumel-hart)参考文献中所描述的三层反向传播网络作为分类级15的神经网络来实现的。在鲁姆哈特参考文献中，对反向传播有详细描述。简单说来，反向传播是这样工作的。在网络训练中，误差(即：一样品输入的适当的输出与该输出现行的网络输出之间的差值)逆向地从输出层传送到中间层然后到输入层。这些误差在每层被练习算法利用以重新调整连接权重使样品图形的未来表示将达到适当的输出类别。在网络训练以后，在正向工作模式中未知的输入图形通过神经网络分类到与其最为相似的样品类别。
神经网络分类器15的输出指明了前期恶性细胞和恶性细胞的存在与否。在输入载片上细胞的位置是通过自动显微镜连续输出的X-Y平面坐标位置中得到的。这种位置信息随着诊断和病人识别信息被输出到打印机或视频显示器17这样使得分类可让病理学家研究。
在所述的实施例中神经网络的平行结构是通过如市售神经计算机加速板的流水串行处理而模拟的。这种神经计算器的工作过程在spectrum中有所讨论神经网络最好是“Delta”处理机，它是国际科学应用公司(SAIC)供应的市场上可以买到的神经计数器(参见上述赫克特—尼尔森Hecht-Nielsen)参考文献该神经计算机可以在正向馈给工作模式中(即非训练模式中)持续不断地以107互连/秒的速率进行处理。对于典型的具有100,000细胞的子宫颈涂片来说，细胞中1-2％或近似1,500个图像将要求由分类器15来处理。(作为所产生的数据率的一个例子，假定数据压缩后，由分类器15处理50×50(图像像素)因此该神经网络的输入层由2,500个处理单元或“神经原”组成。中层由约输入层的25％或625神经原组成(输出神经原的数目等于有关的诊断分类的数目)。这小数目对计算的影响不大)因此互连的数目为2500×625或者约为1.5×106。在107互连/秒的处理速率下，分类器15对分类器14送来的1500幅图像的处理时间不到4分钟。目前可以得到的分类器14的实施例的处理速率为50000细胞/分(参见Tien等的文献)。分类器14以50,000细胞/分的速率处理时，将分类器15的处理所耗费的4分钟加到分类器14所耗费的2分钟上总共达6分钟，6分钟可以分析载片上100,000个细胞图像。如上所述，精确的手工子宫颈涂片的分析约要15分钟/每载片。已有的自动化技术的尝试使用的是非神经网络实施例所需的时间超过1小时/载片。这个例子并不意味着本发明限于这样的构造而是要表明它在所要求的时间内作为商品所要求的时间是可以达到处理子宫颈涂片和其他细胞样品的目标的。
在所述的实施例中，初级分类器14限于评价细胞核，而次级分类器15既评价细胞核也评价它周围的细胞质。细胞核与细胞质之间的比率关系对前期恶性细胞和恶性细胞来说是一个重要的数据。在另一实施例中，分类器14和15都限于对细胞核的鉴定。
从二级分类器中输出的信息送到输出监控器和打印机17，它可以显示出多种信息包括细胞是否是恶性细胞或前期恶性细胞，是否要进一步作检查等等。
图3说明的是另一个实施例，其中，另外加上了一个神经网络分类器16，它的增加是为对大面积物质载片进行处理，即所关心的单一细胞层以外的物质，它包括细胞群、碎片、粘液、白血球等等。在这预筛选中获得的位置信息被存贮起来供分类系统其余部分之用。从分类级16处得到的信息被用于限制要求分类器15处理的处理量。分类级14可以忽略由分类器16输出的平面位置坐标限定区域内的所有的材料这可以减少必须由分类器15处理的信息。因此，判断是根据位于这些区域之外的那些细胞的分类而作出的。如果位于这些区域之外的细胞试样不足，不足以构成有效的判断，则这种信息将作为不足细胞试样而在17上输出。
图4说明又一个实施例，其中分类器16所限定的区域内的图像没有被忽视而是由另一独立的分类器18进行处理，该分类器18与分类器15并行操作。包含分类器18的神经网络的训练专门用来区别所述的人工物质与前期恶性细胞与恶性细胞。
图5是又一个实施例，其中增加了一个非神经网络对除了总光密度以外的核的形态组成部分进行分类该非神经网络分类被安排在分类器14和分类器15之间，该分类由分类器19来执行。
图6是另一个实施例，其中一市场上可以买到的SAIC神经计算机专用于正向馈给处理20(最佳化于正向馈给处理20)。通过对学习工作能力的删除，所有的神经计算器均用作正向馈给操作上。学习通过一独立的未经改动过的神经计算器完成，该神经计算器同时包含学习和正向馈给两种作用。
学习完成之后，最终的互连权重被输送到最佳化的正向馈给神经计数器20中，神经计算器20专门从事正向馈给操作，产生了持续的108互连/秒的正向馈给操作速率，而市场供应的非优化板的速率为107互连/秒。该优化的正向馈给神经网络20用于执行图1，3，4和5中的分类器14和16的作用。通过利用神经网络分类器20去执行统计分类器14的功能，首先细胞仍然得以检测，有关的未必是恶性子宫颈细胞并且不超出分类器14的总光密度阈值的细胞也将被检测出来。一个例子是将子宫内膜细胞也检测了出来，该细胞虽然未必是子宫颈部恶性的征兆，但是在绝经后病人的巴氏涂片中发现时，却指示有可能是子宫恶性肿瘤。
作为从图6的这个实施例中得出的数据速率的例子，假设载片外周尺寸为15mm×45mm或总的载片面积为675×106微米2。神经网络20在其上具有一个分析用的滑动观察孔。这个观察孔的尺寸为20微米×20微米或者是400微米的面积。因此，在15mm×45mm的载片上有1.5×10的这些观察孔。对由神经网络20执行的初级分类功能来说，一个1微米/象素的分辨率就足以充分地探测出那些，必需送到次级神经网络分类器15中供进一步分析的物体。由分类器20分析的图像观察孔的输入图像因此对神经网络20的输入层来说是20×20象素或400神经原。中间层包括输入层的25％或100个神经原(和上述分类器15的数据速率计算一样，输出层的神经原数目很小不影响我们的结论)。分类器20的互连数目接近400×100或40×103。在一个108互连/秒的处理速率下，对神经网20的分类来说，每一个从滑动观察孔中得到的图像要化去400微秒的时间。在一个15mm×45mm的载片上，需要神经网络20分类的有1.5×106个400微米2的观察孔。神经网络20的总的分类时间因此为(1.5×106)(400×10-6)＝600秒或10分钟。如果将这10分钟加到次级神经分类器15所需要的4分钟时间上，那么总的时间为14分钟/载片。这个例子并不说明本发明的结构限于14分钟/载片相反，它只是表明了在一段(符合商品化要求)的时间以内处理子宫颈涂片和其它细胞样品是可以达到的目的。
通过并行的处理处理，数据速度也可以增加。例如，可以将SAIC提供的市场上可以买到的多个神经计算器并联起来对数据进行并行处理，从而，使分类器的处理速度得以增加。
图7说明了又一个实施例，其中神经网络初级分类器也一同被使用，而不是代替形态分类和区域分类，通过分类器20专门对那些有关的少数而其它方法又不能检测出来的细胞类型进行探测，对分类器20的分辨力的要求就可以达到最小。
尽管本发明是用本发明前的较佳实施例来加以描述的，但是应该理解这种揭示并不构成对本发明的限制。本技术领域的技术人员，在阅读上述说明后，可以作出各种变换和修改，这无疑是很显而易见的。为此，下面所附的权项被认为覆盖了所有没有脱离本发明的真实范围的精神的所有变换和改进。

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1.一自动细胞试样分类器，用于对试样中的细胞进行分类以识别可能是恶性或前期恶性的细胞，其特征在于包括：
a.用以获得至少一部分试样之影像的自动显微镜，
b.用以产生所述影像之图像的摄像机，
c.用以产生所述图像之数字表示的图像数字转换器，
d.一初级统计分类器，用以根据一可检测的特征检测所述试样之数字表示中的目标物，所述初级分类器包括一分类器，用以检测可能是恶性或前期恶性的细胞以及开始呈现有恶性细胞或前期恶性细胞特征的其它物质，以及
e.一建立在神经网络基础上的二级分类器，作为神经网络的一种训练功能，在由所述初级分类器识别的目标物之中区分前期恶性细胞和恶性细胞。
2.如权利要求1所述的一自动细胞分类器，其进一步特征在于包括一神经网络预筛选分类器用以对包含除细胞单层以外物质的细胞试样内的区域加以鉴别和分类。
3.如权利要求2所述的自动分类器，其特征在于从预筛选分类器中输出的信息被用于将所述已识别的区域剔出不再让二级分类器进行分析。
4.如权利要求2所述的自动分类器，其特征在于从预筛选分类器中输出的信息用于对在所述预筛选分类器鉴别过的试样区域内找到的图像的二级分类进行修改。
5.如权利要求1所述的自动分类器，其特征在于初级统计筛选分类器仅限于对细胞核的鉴别而二级分类器既鉴别细胞核又鉴别其周围的细胞质。
6.如权利要求1所述的自动分类器，其特征在于初级筛选分类器和次级分类器两者都限于对细胞核的鉴别。
7.如权利要求1所述的自动分类器，其进一步特征在于，除了总光密度以外，还包括对细胞形态组成份进行非神经网络分类的装置，所述的装置连接在初级和次级分类器之间。
8.一自动细胞试样分类器，用于对载片上所作涂片中包含的细胞进行分类以识别可能是恶性或前期恶性的细胞，其特征在于，包括：
a.一显微装置，用以对包括通常随机位于一可包含除单层细胞以外的载片上的细胞和其它物质的细胞试样至少一部分获得影像，
b.用以形成这一影像的图像的摄像装置，
c.用以产生这一图像的数字表示的图像数字转换装置，
d.一初级分类装置，用以根据可检测的特征检测细胞试样的数字表示中的目标物，所述初级分类装置包括一个分类器，用以根据总的光密度检测可能是恶性或前期恶性的细胞，以及开始表现出恶性或前期恶性细胞特征的其它细胞和物质，
e.一个二级分类器，用以从该初级分类装置检测到的目标物中其它细胞和物质内区分出恶性或前期恶性细胞。
9.一种对细胞试样进行分类的方法，其特征在于，包括用一决定有关特征的位置的初级分类装置对通常随机安排和包括除单层细胞以外的试样进行初级分类，以及用一神经网络计算装置对所述位置进行次级分类。
10.如权利要求9所述的方法，其特征在于所述的初级分类包括用一摄像机或电荷耦合器件以获得试样的图像，一使这些图像转换成数字的图像数字转换器和一总光密度检测器。
11.如权利要求9所述的方法，其特征在于所述的初级分类包括神经网络计算装置的使用。
12.如权利要求9所述的方法，其特征在于所述用一初级分类装置对试样进行初级分类的步骤包括使用一统计分类器。
13.如权利要求9所述的方法，其特征在于所述用一初级分类装置对试样进行初级分类的步骤包括根据形状进行分类。
14.如权利要求9所述的方法，其特征在于所述用一初级分类装置对试样进行初级分类的步骤包括根据总光密度进行分类。
15.如权利要求9所述的方法，其特征在于进一步包括训练这种神经网络计算装置识别有关的细胞试样。
16.一自动细胞试样分类器，其特征在于包括：
a.一显微装置，用以对包括通常随机位于一可包含除单层细胞的载片上的细胞和其它物质的细胞试样中至少一部分获得影像，
b.用以形成这一影像的图像的摄像装置，
c.用以产生这一图像的数字表示的图像数字转换装置，
d.一初级分类装置，用以根据一可检测的特征检测细胞试样的数字表示中的目标物，所述初级分类装置包括一个分类器，用以检测可能是预定类型的细胞以及开始表现出该预定类型细胞的特征的其它细胞和物质，
e.一个二级分类装置，用以从该初级分类装置检测到的目标物中其它细胞和物质内区分出预定类型的细胞，所述二极分类装置包括一个神经计算装置，用以实现作为其功能的所述区分。
17.如权利要求8或16所述的自动分类器，其特征在于进一步包括一神经网络预筛选分类装置用以在初级分类之前对包含除细胞单层以外物质的试样的数字表示内一般区域加以识别。
18.如权利要求17所述的自动分类器，其特征在于利用预筛选分类器的输出剔出所述已识别的区域不再进行分析。
19.如权利要求17所述的自动分类器，其特征在于利用预筛选分类器的输出修正对由所述预筛选分类装置识别出的试样区域内找到的图像的进一步分析。
20.如权利要求8或16所述的自动分类器，其特征在于，初级分类装置仅限于对细胞核的鉴别而二极分类装置既鉴别细胞核又鉴别其周围的细胞质。
21.如权利要求8或16所述的自动分类器，其特征在于初级分类装置和二极分装置两者都限于对细胞核的鉴别。
22.如权利要求8或16所述的自动分类器，其特征在于进一步包括用以对核细胞形态组成成份进行辅助的非神经网络分类的装置，所述装置连接在初级分类装置和所述次级分类装置之间。
23.如权利要求8或16所述的自动分类器，其特征在于所述显微装置包括自动显微镜。
24.如权利要求8或16所述的自动分类器，其特征在于所述摄像装置包括电视摄像机。
25.如权利要求8或16所述的自动分类器，其特征在于所述摄像装置包括电荷耦合器件。
26.如权利要求8或16所述的自动分类器，其特征在于所述初级分类器装置包括用以检测细胞试样的数字表示中具有超过阈值的特点的目标物的装置。
27.如权利要求8或16所述的自动分类器，其特征在于所述初级分类装置包括用以检测细胞试样的数字表示中具有超过总光密度阈值的特定的目标物的装置。
28.如权利要求8或16所述的自动分类器，其特征在于所述分类装置包括用以根据形态准则检测细胞试样数字表示中目标物的装置。
29.如权利要求8或16所述的自动分类器，其特征在于所述摄像装置安置为产生所述影像中一部分细胞试样的图像。
30.如权利要求8或16所述的自动分类器，其特征在于所述神经计算装置包括电子神经计算机。
31.如权利要求8或16所述的自动分类器，其特征在于所述次级分类装置能够从重叠的细胞和其它物质中鉴别前期恶性和恶性细胞。
32.如权利要求8或16所述的自动分类器，其特征在于初级分类装置包括一统计分类器。
33.如权利要求8或16所述的自动分类器，其特征在于所述细胞试样包括有重叠的细胞。
34.如权利要求16所述的自动分类器，其特征在于所述次级分类装置能够从重叠的细胞和其它物质中鉴别预定类型的细胞。
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5525464A (en) * 1987-04-01 1996-06-11 Hyseq, Inc. Method of sequencing by hybridization of oligonucleotide probes
US5202231A (en) 1987-04-01 1993-04-13 Drmanac Radoje T Method of sequencing of genomes by hybridization of oligonucleotide probes
US5224175A (en) * 1987-12-07 1993-06-29 Gdp Technologies, Inc. Method for analyzing a body tissue ultrasound image
US5092343A (en) * 1988-02-17 1992-03-03 Wayne State University Waveform analysis apparatus and method using neural network techniques
EP0366804B1 (en) * 1988-03-25 1997-12-10 Hitachi, Ltd. Method of recognizing image structures
US4965725B1 (en) * 1988-04-08 1996-05-07 Neuromedical Systems Inc Neural network based automated cytological specimen classification system and method
US5544650A (en) * 1988-04-08 1996-08-13 Neuromedical Systems, Inc. Automated specimen classification system and method
US5740270A (en) * 1988-04-08 1998-04-14 Neuromedical Systems, Inc. Automated cytological specimen classification system and method
EP0363828B1 (en) * 1988-10-11 1999-01-07 Kabushiki Kaisha Ouyo Keisoku Kenkyusho Method and apparatus for adaptive learning type general purpose image measurement and recognition
US5041916A (en) * 1989-02-07 1991-08-20 Matsushita Electric Industrial Co., Ltd. Color image data compression and recovery apparatus based on neural networks
JPH0821065B2 (ja) * 1989-03-13 1996-03-04 シャープ株式会社 文字認識装置
JP2885823B2 (ja) * 1989-04-11 1999-04-26 株式会社豊田中央研究所 視覚認識装置
JP2940933B2 (ja) * 1989-05-20 1999-08-25 株式会社リコー パターン認識方式
US5547839A (en) 1989-06-07 1996-08-20 Affymax Technologies N.V. Sequencing of surface immobilized polymers utilizing microflourescence detection
US5850465A (en) * 1989-06-26 1998-12-15 Fuji Photo Film Co., Ltd. Abnormnal pattern detecting or judging apparatus, circular pattern judging apparatus, and image finding apparatus
US5086479A (en) * 1989-06-30 1992-02-04 Hitachi, Ltd. Information processing system using neural network learning function
US5140523A (en) * 1989-09-05 1992-08-18 Ktaadn, Inc. Neural network for predicting lightning
WO1991006911A1 (en) * 1989-10-23 1991-05-16 Neuromedical Systems, Inc. Automated cytological specimen classification system and method
JPH03196277A (ja) * 1989-12-25 1991-08-27 Takayama:Kk データ処理装置のための特徴データ選択方法
WO1991011783A1 (en) * 1990-01-23 1991-08-08 Massachusetts Institute Of Technology Recognition of patterns in images
US5313532A (en) * 1990-01-23 1994-05-17 Massachusetts Institute Of Technology Recognition of patterns in images
JPH03223976A (ja) * 1990-01-29 1991-10-02 Ezel Inc 画像照合装置
WO1991014235A1 (en) * 1990-03-06 1991-09-19 Massachusetts Institute Of Technology Recognition of patterns in images
ES2104699T3 (es) * 1990-03-30 1997-10-16 Neuromedical Systems Inc Metodo y sistema automatizados de clasificar una muestra citologica.
JP2896799B2 (ja) * 1990-04-18 1999-05-31 富士写真フイルム株式会社 放射線画像読取条件及び／又は画像処理条件決定装置
US5862304A (en) * 1990-05-21 1999-01-19 Board Of Regents, The University Of Texas System Method for predicting the future occurrence of clinically occult or non-existent medical conditions
WO1991020048A1 (en) * 1990-06-21 1991-12-26 Applied Electronic Vision, Inc. Cellular analysis utilizing video processing and neural network
US5365460A (en) * 1990-08-27 1994-11-15 Rockwell International Corp. Neural network signal processor
US5655029A (en) * 1990-11-07 1997-08-05 Neuromedical Systems, Inc. Device and method for facilitating inspection of a specimen
DE69131102T2 (de) * 1990-11-07 1999-07-29 Neuromedical Systems Inc Untersuchungskontrollverfahren für bilder die auf einer anzeige gezeigt werden
US5214744A (en) * 1990-12-14 1993-05-25 Westinghouse Electric Corp. Method and apparatus for automatically identifying targets in sonar images
US5257182B1 (en) * 1991-01-29 1996-05-07 Neuromedical Systems Inc Morphological classification system and method
US6018587A (en) * 1991-02-21 2000-01-25 Applied Spectral Imaging Ltd. Method for remote sensing analysis be decorrelation statistical analysis and hardware therefor
US5331550A (en) * 1991-03-05 1994-07-19 E. I. Du Pont De Nemours And Company Application of neural networks as an aid in medical diagnosis and general anomaly detection
US5105468A (en) * 1991-04-03 1992-04-14 At&T Bell Laboratories Time delay neural network for printed and cursive handwritten character recognition
US5260871A (en) * 1991-07-31 1993-11-09 Mayo Foundation For Medical Education And Research Method and apparatus for diagnosis of breast tumors
GB9116562D0 (en) * 1991-08-01 1991-09-18 British Textile Tech Sample evaluation
US5776709A (en) * 1991-08-28 1998-07-07 Becton Dickinson And Company Method for preparation and analysis of leukocytes in whole blood
EP0554447B1 (en) * 1991-08-28 1997-04-09 Becton, Dickinson and Company Gravitational attractor engine for adaptively autoclustering n-dimensional data streams
US5941832A (en) * 1991-09-27 1999-08-24 Tumey; David M. Method and apparatus for detection of cancerous and precancerous conditions in a breast
US6418424B1 (en) 1991-12-23 2002-07-09 Steven M. Hoffberg Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
US6850252B1 (en) 1999-10-05 2005-02-01 Steven M. Hoffberg Intelligent electronic appliance system and method
US10361802B1 (en) 1999-02-01 2019-07-23 Blanding Hovenweep, Llc Adaptive pattern recognition based control system and method
US8352400B2 (en) 1991-12-23 2013-01-08 Hoffberg Steven M Adaptive pattern recognition based controller apparatus and method and human-factored interface therefore
US5903454A (en) 1991-12-23 1999-05-11 Hoffberg; Linda Irene Human-factored interface corporating adaptive pattern recognition based controller apparatus
US6400996B1 (en) 1999-02-01 2002-06-04 Steven M. Hoffberg Adaptive pattern recognition based control system and method
EP0628186B1 (en) * 1992-02-18 1998-12-09 Neopath, Inc. Method for identifying normal biomedical specimens
DE69329554T2 (de) * 1992-02-18 2001-05-31 Neopath Inc Verfahren zur identifizierung von objekten unter verwendung von datenverarbeitungstechniken
US5283418A (en) * 1992-02-27 1994-02-01 Westinghouse Electric Corp. Automated rotor welding processes using neural networks
JP3165247B2 (ja) * 1992-06-19 2001-05-14 シスメックス株式会社 粒子分析方法及び装置
DE4224621C2 (de) * 1992-07-25 1994-05-05 Boehringer Mannheim Gmbh Verfahren zur Analyse eines Bestandteils einer medizinischen Probe mittels eines automatischen Analysegerätes
US5388164A (en) * 1992-08-19 1995-02-07 Olympus Optical Co., Ltd. Method for judging particle agglutination patterns using neural networks
US5742702A (en) * 1992-10-01 1998-04-21 Sony Corporation Neural network for character recognition and verification
US5319722A (en) * 1992-10-01 1994-06-07 Sony Electronics, Inc. Neural network for character recognition of rotated characters
US6026174A (en) * 1992-10-14 2000-02-15 Accumed International, Inc. System and method for automatically detecting malignant cells and cells having malignancy-associated changes
US5733721A (en) * 1992-11-20 1998-03-31 The Board Of Regents Of The University Of Oklahoma Cell analysis method using quantitative fluorescence image analysis
US5719784A (en) * 1992-12-14 1998-02-17 University Of Washington At Seattle Order-based analyses of cell and tissue structure
CN1036118C (zh) * 1992-12-29 1997-10-15 陈立奇 肿瘤图像诊断方法及系统
EP0610916A3 (en) * 1993-02-09 1994-10-12 Cedars Sinai Medical Center Method and device for generating preferred segmented numerical images.
US5426010A (en) * 1993-02-26 1995-06-20 Oxford Computer, Inc. Ultra high resolution printing method
US5619619A (en) * 1993-03-11 1997-04-08 Kabushiki Kaisha Toshiba Information recognition system and control system using same
US5479526A (en) * 1993-03-23 1995-12-26 Martin Marietta Pixel designator for small objects
JP3265044B2 (ja) * 1993-03-23 2002-03-11 株式会社コーナン・メディカル 角膜内皮細胞形態決定方法
JP3535873B2 (ja) * 1993-04-10 2004-06-07 フラウンホッファー−ゲゼルシャフト ツァ フェルダールング デァ アンゲヴァンテン フォアシュンク エー．ファオ． 対象分類法
US5475768A (en) * 1993-04-29 1995-12-12 Canon Inc. High accuracy optical character recognition using neural networks with centroid dithering
US5587833A (en) * 1993-07-09 1996-12-24 Compucyte Corporation Computerized microscope specimen encoder
EP0644414B1 (en) * 1993-08-19 2001-11-21 Hitachi, Ltd. Classification and examination device of particles in fluid
US6136540A (en) * 1994-10-03 2000-10-24 Ikonisys Inc. Automated fluorescence in situ hybridization detection of genetic abnormalities
US5352613A (en) * 1993-10-07 1994-10-04 Tafas Triantafillos P Cytological screening method
CA2132269C (en) * 1993-10-12 2000-02-01 Rainer Hermann Doerrer Interactive automated cytology method and system
US5797130A (en) * 1993-11-16 1998-08-18 Neopath, Inc. Method for testing proficiency in screening images of biological slides
JP3165309B2 (ja) * 1993-12-22 2001-05-14 株式会社日立製作所 粒子画像解析装置
KR970006423B1 (ko) * 1993-12-29 1997-04-28 한국전기통신공사 신경망을 이용한 영상 패턴 분류 인식 장치 및 방법
CN1140498A (zh) * 1994-02-14 1997-01-15 神经医药体系股份有限公司 自动化细胞样品分类系统和方法
US5493619A (en) * 1994-03-11 1996-02-20 Haley; Paul H. Normalization method for eliminating false detections in side scan sonar images
US5493539A (en) * 1994-03-11 1996-02-20 Westinghouse Electric Corporation Two-stage detection and discrimination system for side scan sonar equipment
US5486999A (en) * 1994-04-20 1996-01-23 Mebane; Andrew H. Apparatus and method for categorizing health care utilization
US5625705A (en) * 1994-06-03 1997-04-29 Neuromedical Systems, Inc. Intensity texture based classification system and method
US6463438B1 (en) * 1994-06-03 2002-10-08 Urocor, Inc. Neural network for cell image analysis for identification of abnormal cells
US6287850B1 (en) * 1995-06-07 2001-09-11 Affymetrix, Inc. Bioarray chip reaction apparatus and its manufacture
EP0695941B1 (en) * 1994-06-08 2002-07-31 Affymetrix, Inc. Method and apparatus for packaging a chip
CA2195565A1 (en) * 1994-07-26 1996-02-08 Robert Tjon-Fo-Sang Inspection device and method
US5647025A (en) * 1994-09-20 1997-07-08 Neopath, Inc. Automatic focusing of biomedical specimens apparatus
US5692066A (en) * 1994-09-20 1997-11-25 Neopath, Inc. Method and apparatus for image plane modulation pattern recognition
US5627908A (en) * 1994-09-20 1997-05-06 Neopath, Inc. Method for cytological system dynamic normalization
WO1996009594A1 (en) * 1994-09-20 1996-03-28 Neopath, Inc. Apparatus for automated identification of thick cell groupings on a biological specimen
WO1996010237A1 (en) * 1994-09-20 1996-04-04 Neopath, Inc. Biological specimen analysis system processing integrity checking apparatus
US5566249A (en) * 1994-09-20 1996-10-15 Neopath, Inc. Apparatus for detecting bubbles in coverslip adhesive
CA2200455A1 (en) * 1994-09-20 1996-03-28 Louis R. Piloco Apparatus for illumination stabilization and homogenization
AU3586195A (en) * 1994-09-20 1996-04-09 Neopath, Inc. Apparatus for automated identification of cell groupings on a biological specimen
US5740269A (en) * 1994-09-20 1998-04-14 Neopath, Inc. Method and apparatus for robust biological specimen classification
WO1996009600A1 (en) * 1994-09-20 1996-03-28 Neopath, Inc. Apparatus for identification and integration of multiple cell patterns
US5757954A (en) * 1994-09-20 1998-05-26 Neopath, Inc. Field prioritization apparatus and method
US5715327A (en) * 1994-09-20 1998-02-03 Neopath, Inc. Method and apparatus for detection of unsuitable conditions for automated cytology scoring
ES2122950T1 (es) * 1994-09-20 1999-01-01 Neopath Inc Aparato de auto calibrado del sistema de analisis biologico.
US5978497A (en) * 1994-09-20 1999-11-02 Neopath, Inc. Apparatus for the identification of free-lying cells
US5638459A (en) * 1994-09-20 1997-06-10 Neopath, Inc. Method and apparatus for detecting a microscope slide coverslip
AU3490695A (en) * 1994-09-20 1996-04-09 Neopath, Inc. Cytological slide scoring apparatus
AU3675495A (en) * 1994-09-30 1996-04-26 Neopath, Inc. Method and apparatus for highly efficient computer aided screening
US5453676A (en) * 1994-09-30 1995-09-26 Itt Automotive Electrical Systems, Inc. Trainable drive system for a windshield wiper
US5524631A (en) * 1994-10-13 1996-06-11 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration Passive fetal heart rate monitoring apparatus and method with enhanced fetal heart beat discrimination
WO1996012187A1 (en) * 1994-10-13 1996-04-25 Horus Therapeutics, Inc. Computer assisted methods for diagnosing diseases
JP3537194B2 (ja) * 1994-10-17 2004-06-14 オリンパス株式会社 光学顕微鏡
US5795716A (en) 1994-10-21 1998-08-18 Chee; Mark S. Computer-aided visualization and analysis system for sequence evaluation
US6600996B2 (en) 1994-10-21 2003-07-29 Affymetrix, Inc. Computer-aided techniques for analyzing biological sequences
JP3189608B2 (ja) * 1995-02-01 2001-07-16 株式会社日立製作所 フロー式粒子画像解析方法
US5708591A (en) * 1995-02-14 1998-01-13 Akzo Nobel N.V. Method and apparatus for predicting the presence of congenital and acquired imbalances and therapeutic conditions
US5884296A (en) * 1995-03-13 1999-03-16 Minolta Co., Ltd. Network and image area attribute discriminating device and method for use with said neural network
FR2733596B1 (fr) * 1995-04-28 1997-07-18 Hycel Groupe Lisabio Procede et dispositif d'identification de particules
US5625706A (en) * 1995-05-31 1997-04-29 Neopath, Inc. Method and apparatus for continously monitoring and forecasting slide and specimen preparation for a biological specimen population
US5671288A (en) * 1995-05-31 1997-09-23 Neopath, Inc. Method and apparatus for assessing slide and specimen preparation quality
US5619428A (en) * 1995-05-31 1997-04-08 Neopath, Inc. Method and apparatus for integrating an automated system to a laboratory
US5787208A (en) * 1995-06-07 1998-07-28 Neopath, Inc. Image enhancement method and apparatus
US6252979B1 (en) 1995-06-07 2001-06-26 Tripath Imaging, Inc. Interactive method and apparatus for sorting biological specimens
US6898532B1 (en) 1995-06-07 2005-05-24 Biomerieux, Inc. Method and apparatus for predicting the presence of haemostatic dysfunction in a patient sample
US6321164B1 (en) 1995-06-07 2001-11-20 Akzo Nobel N.V. Method and apparatus for predicting the presence of an abnormal level of one or more proteins in the clotting cascade
US6242876B1 (en) 1995-06-07 2001-06-05 Valeo Electrical Systems, Inc. Intermittent windshield wiper controller
US6429017B1 (en) * 1999-02-04 2002-08-06 Biomerieux Method for predicting the presence of haemostatic dysfunction in a patient sample
US6720149B1 (en) * 1995-06-07 2004-04-13 Affymetrix, Inc. Methods for concurrently processing multiple biological chip assays
US5889880A (en) * 1995-06-07 1999-03-30 Autocyte, Inc. Interactive automated cytology method incorporating both manual and automatic determinations
US5621519A (en) * 1995-07-31 1997-04-15 Neopath, Inc. Imaging system transfer function control method and apparatus
US5745601A (en) * 1995-07-31 1998-04-28 Neopath, Inc. Robustness of classification measurement apparatus and method
US5642433A (en) * 1995-07-31 1997-06-24 Neopath, Inc. Method and apparatus for image contrast quality evaluation
US6091842A (en) * 1996-10-25 2000-07-18 Accumed International, Inc. Cytological specimen analysis system with slide mapping and generation of viewing path information
US5930732A (en) * 1995-09-15 1999-07-27 Accumed International, Inc. System for simplifying the implementation of specified functions
US5690892A (en) * 1995-09-15 1997-11-25 Accumed, Inc. Cassette for use with automated specimen handling system
US5963368A (en) * 1995-09-15 1999-10-05 Accumed International, Inc. Specimen management system
US6118581A (en) * 1995-09-15 2000-09-12 Accumed International, Inc. Multifunctional control unit for a microscope
US6430309B1 (en) 1995-09-15 2002-08-06 Monogen, Inc. Specimen preview and inspection system
CA2185511C (en) * 1995-09-15 2008-08-05 Vladimir Dadeshidze Cytological specimen analysis system with individualized patient data
US6148096A (en) * 1995-09-15 2000-11-14 Accumed International, Inc. Specimen preview and inspection system
US5732150A (en) * 1995-09-19 1998-03-24 Ihc Health Services, Inc. Method and system for multiple wavelength microscopy image analysis
CA2232164A1 (en) * 1995-09-19 1997-03-27 Morphometrix Technologies Inc. A neural network assisted multi-spectral segmentation system
JPH0991430A (ja) * 1995-09-27 1997-04-04 Hitachi Ltd パターン認識装置
US20040175718A1 (en) * 1995-10-16 2004-09-09 Affymetrix, Inc. Computer-aided visualization and analysis system for sequence evaluation
IL115985A0 (en) 1995-11-14 1996-01-31 Elop Electrooptics Ind Ltd System and method for computerized archiving
US6151405A (en) * 1996-11-27 2000-11-21 Chromavision Medical Systems, Inc. System and method for cellular specimen grading
US6718053B1 (en) * 1996-11-27 2004-04-06 Chromavision Medical Systems, Inc. Method and apparatus for automated image analysis of biological specimens
US6215892B1 (en) 1995-11-30 2001-04-10 Chromavision Medical Systems, Inc. Method and apparatus for automated image analysis of biological specimens
US5699794A (en) * 1995-12-19 1997-12-23 Neopath, Inc. Apparatus for automated urine sediment sample handling
US5835620A (en) * 1995-12-19 1998-11-10 Neuromedical Systems, Inc. Boundary mapping system and method
AU1294797A (en) * 1995-12-21 1997-07-17 Erudite Technology Iii, Inc. A method for the detection, identification and alteration of molecular structure in various media
US5850464A (en) * 1996-01-16 1998-12-15 Erim International, Inc. Method of extracting axon fibers and clusters
US6678669B2 (en) * 1996-02-09 2004-01-13 Adeza Biomedical Corporation Method for selecting medical and biochemical diagnostic tests using neural network-related applications
US6361937B1 (en) * 1996-03-19 2002-03-26 Affymetrix, Incorporated Computer-aided nucleic acid sequencing
US5724253A (en) * 1996-03-26 1998-03-03 International Business Machines Corporation System and method for searching data vectors such as genomes for specified template vector
DE19616997A1 (de) * 1996-04-27 1997-10-30 Boehringer Mannheim Gmbh Verfahren zur automatisierten mikroskopunterstützten Untersuchung von Gewebeproben oder Körperflüssigkeitsproben
US5796861A (en) * 1996-07-12 1998-08-18 Frim International, Inc. Mosaic construction, processing, and review of very large electronic micrograph composites
US5810747A (en) * 1996-08-21 1998-09-22 Interactive Remote Site Technology, Inc. Remote site medical intervention system
US6272235B1 (en) * 1997-03-03 2001-08-07 Bacus Research Laboratories, Inc. Method and apparatus for creating a virtual microscope slide
US6404906B2 (en) * 1997-03-03 2002-06-11 Bacus Research Laboratories,Inc. Method and apparatus for acquiring and reconstructing magnified specimen images from a computer-controlled microscope
US6031930A (en) * 1996-08-23 2000-02-29 Bacus Research Laboratories, Inc. Method and apparatus for testing a progression of neoplasia including cancer chemoprevention testing
US6396941B1 (en) 1996-08-23 2002-05-28 Bacus Research Laboratories, Inc. Method and apparatus for internet, intranet, and local viewing of virtual microscope slides
US6122396A (en) * 1996-12-16 2000-09-19 Bio-Tech Imaging, Inc. Method of and apparatus for automating detection of microorganisms
WO1998029833A1 (fr) * 1996-12-25 1998-07-09 Hitachi, Ltd. Appareil et procede de reconnaissance de formes
JP3702978B2 (ja) * 1996-12-26 2005-10-05 ソニー株式会社 認識装置および認識方法、並びに学習装置および学習方法
US5937103A (en) * 1997-01-25 1999-08-10 Neopath, Inc. Method and apparatus for alias free measurement of optical transfer function
US6753161B2 (en) * 1997-03-27 2004-06-22 Oncosis Llc Optoinjection methods
GB9714347D0 (en) * 1997-07-09 1997-09-10 Oxoid Ltd Image analysis systems and devices for use therewith
US5959726A (en) * 1997-07-25 1999-09-28 Neopath, Inc. Modulation transfer function test compensation for test pattern duty cycle
WO1999010771A1 (en) * 1997-08-22 1999-03-04 Lxr Biotechnology, Inc. Focusing and autofocusing in scanning laser imaging
US6198839B1 (en) * 1997-09-05 2001-03-06 Tripath Imaging, Inc. Dynamic control and decision making method and apparatus
US6502040B2 (en) 1997-12-31 2002-12-31 Biomerieux, Inc. Method for presenting thrombosis and hemostasis assay data
US6181811B1 (en) 1998-01-13 2001-01-30 Neopath, Inc. Method and apparatus for optimizing biological and cytological specimen screening and diagnosis
US6166142A (en) 1998-01-27 2000-12-26 E. I. Du Pont De Nemours And Company Adhesive compositions based on blends of grafted metallocene catalyzed and polar ethylene copolymers
US20080241848A1 (en) * 1998-05-09 2008-10-02 Ikonisys, Inc. Methods for prenatal diagnosis of aneuploidy
US7901887B2 (en) * 1998-05-09 2011-03-08 Ikonisys, Inc. Automated cancer diagnostic methods using fish
KR100691043B1 (ko) * 1998-05-09 2007-03-09 아이코니시스 인코포레이티드 컴퓨터 제어된 태아 세포 포함 희귀 세포 진단 방법 및 장치
US20090111101A1 (en) * 1998-05-09 2009-04-30 Ikonisys, Inc. Automated Cancer Diagnostic Methods Using FISH
DE69915381D1 (de) * 1998-09-02 2004-04-08 Accip Biothech As Aarhus Gerat zum isolieren von partikeln, insbesondre von zellhaufen
US6091843A (en) * 1998-09-03 2000-07-18 Greenvision Systems Ltd. Method of calibration and real-time analysis of particulates
US6572824B1 (en) * 1998-09-18 2003-06-03 Cytyc Corporation Method and apparatus for preparing cytological specimens
US6357285B1 (en) 1998-11-09 2002-03-19 Veeco Instruments Inc. Method and apparatus for the quantitative and objective correlation of data from a local sensitive force detector
FR2785713B1 (fr) * 1998-11-10 2000-12-08 Commissariat Energie Atomique Systeme de commande d'unites de levage et de telemanipulation placees en enceinte confinee
US7510841B2 (en) 1998-12-28 2009-03-31 Illumina, Inc. Methods of making and using composite arrays for the detection of a plurality of target analytes
US7904187B2 (en) 1999-02-01 2011-03-08 Hoffberg Steven M Internet appliance system and method
ATE282208T1 (de) * 1999-02-04 2004-11-15 Bio Merieux Inc Verfahren und vorrichtung zum vorhersagen von haemostatischer funktionsstörung in patientenproben
US6297044B1 (en) * 1999-02-23 2001-10-02 Oralscan Laboratories, Inc. Minimally invasive apparatus for testing lesions of the oral cavity and similar epithelium
AU762085B2 (en) * 1999-04-13 2003-06-19 Chromavision Medical Systems, Inc. Histological reconstruction and automated image analysis
US6651008B1 (en) 1999-05-14 2003-11-18 Cytokinetics, Inc. Database system including computer code for predictive cellular bioinformatics
US6743576B1 (en) 1999-05-14 2004-06-01 Cytokinetics, Inc. Database system for predictive cellular bioinformatics
US6876760B1 (en) 2000-12-04 2005-04-05 Cytokinetics, Inc. Classifying cells based on information contained in cell images
US7151847B2 (en) * 2001-02-20 2006-12-19 Cytokinetics, Inc. Image analysis of the golgi complex
DE19937778B4 (de) * 1999-08-10 2011-11-24 Cellasys Gmbh Verfahren und Vorrichtung zur Charakterisierung des funktionalen Zustandes von Zellen und Alterationen von Zellen
US7369304B2 (en) * 1999-10-29 2008-05-06 Cytyc Corporation Cytological autofocusing imaging systems and methods
US6661501B1 (en) 1999-10-29 2003-12-09 Cytyc Corporation Cytological stain composition including verification characteristic
US6348325B1 (en) 1999-10-29 2002-02-19 Cytyc Corporation Cytological stain composition
US6593102B2 (en) 1999-10-29 2003-07-15 Cytyc Corporation Cytological stain composition
US6665060B1 (en) * 1999-10-29 2003-12-16 Cytyc Corporation Cytological imaging system and method
WO2001036939A2 (de) * 1999-11-04 2001-05-25 Meltec Multi-Epitope-Ligand-Technologies Gmbh Verfahren zur automatischen analyse von mikroskopaufnahmen
WO2001040454A1 (en) 1999-11-30 2001-06-07 Oncosis Method and apparatus for selectively targeting specific cells within a cell population
US6535626B1 (en) 2000-01-14 2003-03-18 Accumed International, Inc. Inspection system with specimen preview
US7016551B1 (en) * 2000-04-10 2006-03-21 Fuji Xerox Co., Ltd. Image reader
US6947586B2 (en) * 2000-04-24 2005-09-20 International Remote Imaging Systems, Inc. Multi-neural net imaging apparatus and method
US7236623B2 (en) * 2000-04-24 2007-06-26 International Remote Imaging Systems, Inc. Analyte recognition for urinalysis diagnostic system
US7179612B2 (en) 2000-06-09 2007-02-20 Biomerieux, Inc. Method for detecting a lipoprotein-acute phase protein complex and predicting an increased risk of system failure or mortality
EP1322788A2 (en) * 2000-06-23 2003-07-02 Cytokinetics, Inc. Image analysis for phenotyping sets of mutant cells
IL138123A0 (en) * 2000-08-28 2001-10-31 Accuramed 1999 Ltd Medical decision support system and method
US6804385B2 (en) 2000-10-24 2004-10-12 Oncosis Method and device for selectively targeting cells within a three-dimensional specimen
US7027628B1 (en) 2000-11-14 2006-04-11 The United States Of America As Represented By The Department Of Health And Human Services Automated microscopic image acquisition, compositing, and display
WO2002044695A1 (en) * 2000-11-16 2002-06-06 Burstein Technologies, Inc. Methods and apparatus for detecting and quantifying lymphocytes with optical biodiscs
US7099510B2 (en) * 2000-11-29 2006-08-29 Hewlett-Packard Development Company, L.P. Method and system for object detection in digital images
US7218764B2 (en) * 2000-12-04 2007-05-15 Cytokinetics, Inc. Ploidy classification method
US20040262318A1 (en) * 2000-12-08 2004-12-30 Ardais Corporation Container, method and system for cryptopreserved material
US6599694B2 (en) 2000-12-18 2003-07-29 Cytokinetics, Inc. Method of characterizing potential therapeutics by determining cell-cell interactions
US6466690C1 (en) * 2000-12-19 2008-11-18 Bacus Res Lab Inc Method and apparatus for processing an image of a tissue sample microarray
US6816606B2 (en) * 2001-02-21 2004-11-09 Interscope Technologies, Inc. Method for maintaining high-quality focus during high-throughput, microscopic digital montage imaging
US6993169B2 (en) * 2001-01-11 2006-01-31 Trestle Corporation System and method for finding regions of interest for microscopic digital montage imaging
US7155049B2 (en) * 2001-01-11 2006-12-26 Trestle Acquisition Corp. System for creating microscopic digital montage images
US6798571B2 (en) 2001-01-11 2004-09-28 Interscope Technologies, Inc. System for microscopic digital montage imaging using a pulse light illumination system
US7016787B2 (en) * 2001-02-20 2006-03-21 Cytokinetics, Inc. Characterizing biological stimuli by response curves
US6956961B2 (en) * 2001-02-20 2005-10-18 Cytokinetics, Inc. Extracting shape information contained in cell images
US20020165839A1 (en) * 2001-03-14 2002-11-07 Taylor Kevin M. Segmentation and construction of segmentation classifiers
WO2002074055A2 (en) * 2001-03-19 2002-09-26 Ikonisys, Inc. Epifluorecence microscope with improved image contrast
EP1380005A1 (en) * 2001-04-09 2004-01-14 Lifespan Biosciences, Inc. Computer method for image pattern recognition in organic material
US20020186875A1 (en) * 2001-04-09 2002-12-12 Burmer Glenna C. Computer methods for image pattern recognition in organic material
US20030143637A1 (en) * 2001-08-31 2003-07-31 Selvan Gowri Pyapali Capture layer assemblies for cellular assays including related optical analysis discs and methods
US20040071328A1 (en) * 2001-09-07 2004-04-15 Vaisberg Eugeni A. Classifying cells based on information contained in cell images
AU2002335715A1 (en) * 2001-09-07 2003-03-24 Burstein Technologies, Inc. Optical bio-disc systems for nuclear morphology based identification
US6767733B1 (en) 2001-10-10 2004-07-27 Pritest, Inc. Portable biosensor apparatus with controlled flow
US10156501B2 (en) 2001-11-05 2018-12-18 Life Technologies Corporation Automated microdissection instrument for determining a location of a laser beam projection on a worksurface area
US8715955B2 (en) 2004-09-09 2014-05-06 Life Technologies Corporation Laser microdissection apparatus and method
US8722357B2 (en) * 2001-11-05 2014-05-13 Life Technologies Corporation Automated microdissection instrument
AU2002361618A1 (en) 2001-11-13 2003-05-26 Chromavision Medical Systems, Inc. A system for tracking biological samples
US7157049B2 (en) * 2001-11-20 2007-01-02 Nagaoka & Co., Ltd. Optical bio-discs and fluidic circuits for analysis of cells and methods relating thereto
US20040010481A1 (en) * 2001-12-07 2004-01-15 Whitehead Institute For Biomedical Research Time-dependent outcome prediction using neural networks
US20040020993A1 (en) * 2001-12-28 2004-02-05 Green Larry R. Method for luminescent identification and calibration
WO2003069421A2 (en) * 2002-02-14 2003-08-21 Immunivest Corporation Methods and algorithms for cell enumeration in a low-cost cytometer
US7764821B2 (en) * 2002-02-14 2010-07-27 Veridex, Llc Methods and algorithms for cell enumeration in a low-cost cytometer
WO2003073365A1 (en) * 2002-02-22 2003-09-04 Bacus Research Laboratories, Inc. Focusable virtual microscopy apparatus and method
US20040060987A1 (en) * 2002-05-07 2004-04-01 Green Larry R. Digital image analysis method for enhanced and optimized signals in fluorophore detection
JP2005525550A (ja) * 2002-05-14 2005-08-25 アマーシャム バイオサイエンセズ ナイアガラ，インク． 細胞の迅速自動化スクリーニングシステム及び方法
AU2003231827A1 (en) * 2002-05-23 2003-12-12 Invitrogen Corporation Pseudo-tissues and uses thereof
US20050037406A1 (en) * 2002-06-12 2005-02-17 De La Torre-Bueno Jose Methods and apparatus for analysis of a biological specimen
US7272252B2 (en) * 2002-06-12 2007-09-18 Clarient, Inc. Automated system for combining bright field and fluorescent microscopy
WO2004025569A2 (en) * 2002-09-13 2004-03-25 Arcturus Bioscience, Inc. Tissue image analysis for cell classification and laser capture microdissection
US7200252B2 (en) * 2002-10-28 2007-04-03 Ventana Medical Systems, Inc. Color space transformations for use in identifying objects of interest in biological specimens
US8712118B2 (en) * 2003-04-10 2014-04-29 Carl Zeiss Microimaging Gmbh Automated measurement of concentration and/or amount in a biological sample
US20040202357A1 (en) 2003-04-11 2004-10-14 Perz Cynthia B. Silhouette image acquisition
US7324694B2 (en) * 2003-05-23 2008-01-29 International Remote Imaging Systems, Inc. Fluid sample analysis using class weights
US20040241659A1 (en) * 2003-05-30 2004-12-02 Applera Corporation Apparatus and method for hybridization and SPR detection
US7235353B2 (en) * 2003-07-18 2007-06-26 Cytokinetics, Inc. Predicting hepatotoxicity using cell based assays
EP1646926A2 (en) * 2003-07-18 2006-04-19 Cytokinetics, Inc. Characterizing biological stimuli by response curves
US20050014217A1 (en) * 2003-07-18 2005-01-20 Cytokinetics, Inc. Predicting hepatotoxicity using cell based assays
US7106502B1 (en) * 2003-08-21 2006-09-12 The United States Of America As Represented By The Administrator Of National Aeronautics And Space Administration Operation of a Cartesian robotic system in a compact microscope imaging system with intelligent controls
CN1296699C (zh) * 2003-12-19 2007-01-24 武汉大学 显微多光谱骨髓及外周血细胞自动分析仪和分析骨髓及外周血细胞的方法
US7425426B2 (en) * 2004-03-15 2008-09-16 Cyntellect, Inc. Methods for purification of cells based on product secretion
US20050273271A1 (en) * 2004-04-05 2005-12-08 Aibing Rao Method of characterizing cell shape
US7653260B2 (en) 2004-06-17 2010-01-26 Carl Zeis MicroImaging GmbH System and method of registering field of view
US8582924B2 (en) 2004-06-30 2013-11-12 Carl Zeiss Microimaging Gmbh Data structure of an image storage and retrieval system
US7316904B1 (en) 2004-06-30 2008-01-08 Chromodynamics, Inc. Automated pap screening using optical detection of HPV with or without multispectral imaging
US20070031818A1 (en) * 2004-07-15 2007-02-08 Cytokinetics, Inc., A Delaware Corporation Assay for distinguishing live and dead cells
US7323318B2 (en) * 2004-07-15 2008-01-29 Cytokinetics, Inc. Assay for distinguishing live and dead cells
US8189899B2 (en) * 2004-07-30 2012-05-29 Veridex, Llc Methods and algorithms for cell enumeration in a low-cost cytometer
US7792338B2 (en) * 2004-08-16 2010-09-07 Olympus America Inc. Method and apparatus of mechanical stage positioning in virtual microscopy image capture
US7328198B1 (en) 2004-12-31 2008-02-05 Cognitech, Inc. Video demultiplexing based on meaningful modes extraction
GB0503629D0 (en) * 2005-02-22 2005-03-30 Durand Technology Ltd Method and apparatus for automated analysis of biological specimen
JP4214124B2 (ja) * 2005-03-14 2009-01-28 株式会社バイオエコーネット 耳式体温計
CN100351057C (zh) * 2005-03-14 2007-11-28 南开大学 基于显微图像处理的微操作工具深度信息提取方法及装置
US20060246576A1 (en) * 2005-04-06 2006-11-02 Affymetrix, Inc. Fluidic system and method for processing biological microarrays in personal instrumentation
US20070031043A1 (en) * 2005-08-02 2007-02-08 Perz Cynthia B System for and method of intelligently directed segmentation analysis for automated microscope systems
US20070091109A1 (en) * 2005-09-13 2007-04-26 Roscoe Atkinson Image quality
JP4915071B2 (ja) * 2005-09-22 2012-04-11 株式会社ニコン 顕微鏡、およびバーチャルスライド作成システム
US7783092B2 (en) * 2006-01-17 2010-08-24 Illinois Institute Of Technology Method for enhancing diagnostic images using vessel reconstruction
US20080003667A1 (en) * 2006-05-19 2008-01-03 Affymetrix, Inc. Consumable elements for use with fluid processing and detection systems
JP2010500081A (ja) * 2006-08-11 2010-01-07 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ 系統的なデータ・スケーリングを遺伝的アルゴリズムに基づく特徴サブセット選択に統合する方法および装置
US8795197B2 (en) 2007-07-17 2014-08-05 Histologics, LLC Frictional trans-epithelial tissue disruption collection apparatus and method of inducing an immune response
ES2633650T3 (es) * 2007-07-17 2017-09-22 Neal Marc Lonky Aparato de rotura y recolección de tejidos trans-epiteliales por fricción y método para inducir y/o aumentar una respuesta inmune
AU2009218872B2 (en) 2008-02-29 2015-01-15 Agilent Technologies, Inc. Systems and methods for tracking and providing workflow information
US8135202B2 (en) * 2008-06-02 2012-03-13 Nec Laboratories America, Inc. Automated method and system for nuclear analysis of biopsy images
CN102341505A (zh) * 2009-01-09 2012-02-01 英特拉克森公司 细胞的遗传学分析
KR20110108390A (ko) 2009-01-12 2011-10-05 신텔렉트 인코포레이티드 레이저로 매개된 박막 절개 및 세포 군체의 이동
EP2406679B1 (de) 2009-03-11 2017-01-25 Sakura Finetek U.S.A., Inc. Autofokusverfahren und autofokuseinrichtung
US9607202B2 (en) 2009-12-17 2017-03-28 University of Pittsburgh—of the Commonwealth System of Higher Education Methods of generating trophectoderm and neurectoderm from human embryonic stem cells
US9044213B1 (en) 2010-03-26 2015-06-02 Histologics, LLC Frictional tissue sampling and collection method and device
EP2585578A4 (en) 2010-05-08 2014-01-08 Univ Twente EASY AND AFFORDABLE METHOD FOR IMMUNOPHENOTYPIZING ON SAMPLE PREPARATION WITH A MICROFLUIDIC CHIP WITH IMAGE CYTOMETRY
US10139613B2 (en) 2010-08-20 2018-11-27 Sakura Finetek U.S.A., Inc. Digital microscope and method of sensing an image of a tissue sample
US8388891B2 (en) * 2010-12-28 2013-03-05 Sakura Finetek U.S.A., Inc. Automated system and method of processing biological specimens
AU2012271257B2 (en) 2011-06-17 2016-01-14 Roche Diagnostics Hematology, Inc. Systems and methods for sample display and review
US9459196B2 (en) 2011-07-22 2016-10-04 Roche Diagnostics Hematology, Inc. Blood analyzer calibration and assessment
CN102359938B (zh) * 2011-09-16 2012-09-05 长沙高新技术产业开发区爱威科技实业有限公司 红细胞形态学分析装置及其方法
US9170256B2 (en) * 2011-09-16 2015-10-27 Ave Science & Technology Co., Ltd Device and method for erythrocyte morphology analysis
WO2013104937A2 (en) * 2012-01-11 2013-07-18 77 Elektronika Mũszeripari Kft. Image processing method and apparatus
WO2013106842A2 (en) * 2012-01-13 2013-07-18 The Charles Stark Draper Laboratory, Inc. Stem cell bioinformatics
US10201332B1 (en) 2012-12-03 2019-02-12 Healoe Llc Device and method of orienting a biopsy device on epithelial tissue
US9904842B2 (en) 2012-12-19 2018-02-27 Koninklijke Philips N.V. System and method for classification of particles in a fluid sample
JP2016522880A (ja) * 2013-03-15 2016-08-04 リチャード・ハリー・ターナー 体液内の粒子及び可溶化学物質の体外での検出のためのシステムおよび方法
DE102013103971A1 (de) 2013-04-19 2014-11-06 Sensovation Ag Verfahren zum Erzeugen eines aus mehreren Teilbildern zusammengesetzten Gesamtbilds eines Objekts
US10007102B2 (en) 2013-12-23 2018-06-26 Sakura Finetek U.S.A., Inc. Microscope with slide clamping assembly
DE102014202860B4 (de) * 2014-02-17 2016-12-29 Leica Microsystems Cms Gmbh Bereitstellen von Probeninformationen mit einem Lasermikrodissektionssystem
WO2016115537A2 (en) * 2015-01-15 2016-07-21 Massachusetts Institute Of Technology Systems, methods, and apparatus for in vitro single-cell identification and recovery
US10304188B1 (en) 2015-03-27 2019-05-28 Caleb J. Kumar Apparatus and method for automated cell analysis
US10007863B1 (en) * 2015-06-05 2018-06-26 Gracenote, Inc. Logo recognition in images and videos
CN105259095A (zh) * 2015-10-14 2016-01-20 南昌西尔戴尔医疗科技有限公司 宫颈癌细胞病理学排阴法智能筛查系统
US11013466B2 (en) 2016-01-28 2021-05-25 Healoe, Llc Device and method to control and manipulate a catheter
CN105717116A (zh) * 2016-02-23 2016-06-29 中国农业大学 动物源性肉骨粉的种属鉴别方法和系统
EP3478728A4 (en) 2016-06-30 2019-07-17 Konica Minolta Laboratory U.S.A., Inc. LEARNING METHOD AND SYSTEM FOR CELL ANNOTATION WITH ADAPTIVE INCREMENTAL LEARNING
US11280803B2 (en) 2016-11-22 2022-03-22 Sakura Finetek U.S.A., Inc. Slide management system
US10345218B2 (en) 2016-12-06 2019-07-09 Abbott Laboratories Automated slide assessments and tracking in digital microscopy
US20190385707A1 (en) * 2017-03-03 2019-12-19 Fenologica Biosciences, Inc. Phenotype measurement systems and methods
CN107909017A (zh) * 2017-11-06 2018-04-13 余帝乾 一种复杂背景下车牌识别的方法、装置以及系统
US10402623B2 (en) 2017-11-30 2019-09-03 Metal Industries Research & Development Centre Large scale cell image analysis method and system
TWI699816B (zh) * 2017-12-26 2020-07-21 雲象科技股份有限公司 自動化顯微鏡系統之控制方法、顯微鏡系統及電腦可讀取記錄媒體
KR102041402B1 (ko) * 2018-08-09 2019-11-07 주식회사 버즈폴 자궁경부 학습 데이터 생성 시스템과 자궁경부 학습 데이터 분류방법
CN113811754A (zh) * 2018-08-30 2021-12-17 贝克顿·迪金森公司 颗粒分析仪的表征和分选
SE544735C2 (en) * 2018-11-09 2022-11-01 Mm18 Medical Ab Method for identification of different categories of biopsy sample images
CN111767929A (zh) * 2019-03-14 2020-10-13 上海市第一人民医院 黄斑下新生血管模型的构建方法及系统
CN110633651B (zh) * 2019-08-26 2022-05-13 武汉大学 一种基于图像拼接的异常细胞自动识别方法
CN111209879B (zh) * 2020-01-12 2023-09-19 杭州电子科技大学 基于深度圈视图的无监督3d物体识别与检索方法

Family Cites Families (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB203586A (en) * 1922-11-20 1923-09-13 Gerhard Kerff Improvements in and relating to the manufacture of corrugated headers for water tube boilers
US3333248A (en) * 1963-12-20 1967-07-25 Ibm Self-adaptive systems
US4000417A (en) * 1975-08-25 1976-12-28 Honeywell Inc. Scanning microscope system with automatic cell find and autofocus
US4048616A (en) * 1975-12-03 1977-09-13 Geometric Data Corporation Pattern recognition system with keyboard entry for adaptive sensitivity
DE2903625A1 (de) * 1978-02-03 1979-08-09 Rush Presbyterian St Luke Vorrichtung zur automatischen blutanalyse
JPS5661650A (en) * 1979-10-24 1981-05-27 Omron Tateisi Electronics Co Analyzing device of cell
US4612614A (en) * 1980-09-12 1986-09-16 International Remote Imaging Systems, Inc. Method of analyzing particles in a fluid sample
US4501495A (en) * 1981-06-17 1985-02-26 Smithkline Beckman Corporation Slide carrier
US4513438A (en) * 1982-04-15 1985-04-23 Coulter Electronics, Inc. Automated microscopy system and method for locating and re-locating objects in an image
US4591980A (en) * 1984-02-16 1986-05-27 Xerox Corporation Adaptive self-repairing processor array
US4700298A (en) * 1984-09-14 1987-10-13 Branko Palcic Dynamic microscope image processing scanner
GB8514591D0 (en) * 1985-06-10 1985-07-10 Shandon Southern Prod Centrifugation
US4807979A (en) * 1986-01-24 1989-02-28 Geno Saccomanno Microscope slide marking device
US4833625A (en) * 1986-07-09 1989-05-23 University Of Arizona Image viewing station for picture archiving and communications systems (PACS)
US4821118A (en) * 1986-10-09 1989-04-11 Advanced Identification Systems, Inc. Video image system for personal identification
US4805225A (en) * 1986-11-06 1989-02-14 The Research Foundation Of The State University Of New York Pattern recognition method and apparatus
US4965725B1 (en) * 1988-04-08 1996-05-07 Neuromedical Systems Inc Neural network based automated cytological specimen classification system and method

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