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1. 发明申请

WO2017036921A1 IMAGE PROCESSING SYSTEMS AND METHODS FOR DISPLAYING MULTIPLE IMAGES OF A BIOLOGICAL SPECIMEN 审中-公开
标题翻译：用于显示生物样本的多个图像的图像处理系统和方法
公开(公告)号：WO2017036921A1
公开(公告)日：2017-03-09
申请号：PCT/EP2016/070105
申请日：2016-08-25
申请人： VENTANA MEDICAL SYSTEMS, INC. , PROVIDENCE HEALTH & SERVICES - OREGON , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , CHEN, Ting , CHEFD'HOTEL, Christophe , TUBBS, Alisa , BIFULCO, Carlo
IPC分类号： G06T11/60 , G06F19/26
CPC分类号： G06T11/60 , G06F19/26
摘要： A system and method of displaying of multiple simultaneous views of a same region of a biological tissue sample. Logical instructions are executed by a processor to perform operations such as receiving a plurality of images of the biological tissue sample, converting the plurality of images to a common reference frame based on the individual metadata of each image, and arranging the plurality of images into a display pattern for simultaneous viewing of different aspects of the imaged biological tissue sample on a display screen. The plurality of images is produced by preprocessing images of the biological tissue sample. Each image shows a view mode of a same region of the biological tissue sample, and each image contains metadata that describe spatial orientation, such as the translation, rotation, and magnification, of the image to bring the plurality of images to a common view.
摘要翻译：显示生物组织样本的相同区域的多个同时视图的系统和方法。逻辑指令由处理器执行以执行诸如接收生物组织样本的多个图像的操作，基于每个图像的各个元数据将多个图像转换为公共参考帧，并将多个图像排列成显示图案，用于在显示屏幕上同时观看成像的生物组织样品的不同方面。通过预处理生物组织样本的图像来产生多个图像。每个图像显示生物组织样本的相同区域的视图模式，并且每个图像包含描述图像的空间定向（诸如图像的平移，旋转和放大）以使多个图像成为共同视图的元数据。

2. 发明申请

WO2016087589A1 METHODS, SYSTEMS, AND APPARATUSES FOR QUANTITATIVE ANALYSIS OF HETEROGENEOUS BIOMARKER DISTRIBUTION 审中-公开
标题翻译：异源生物标志物分布定量分析的方法，系统和装置
公开(公告)号：WO2016087589A1
公开(公告)日：2016-06-09
申请号：PCT/EP2015/078532
申请日：2015-12-03
申请人： VENTANA MEDICAL SYSTEMS, INC. , OREGON HEALTH & SCIENCE UNIVERSITY , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , CHAFIN, David , GARSHA, Karl , GROGAN, Thomas M. , ROBERTS, Esteban , STEVENS, Benjamin , VENTURA, Frank , CHEFD´HOTEL, Christophe , SHANMUGAM, Kandavel , GRAY, Joe , RAMUNNO-JOHNSON, Damien , QUOC VU, Tothu (Tania)
IPC分类号： G06K9/00 , G06K9/62 , G06T7/00 , G01N33/50 , G06T7/40
CPC分类号： G06T7/0012 , G06K9/00147 , G06K9/3233 , G06K9/4652 , G06K9/6222 , G06T7/11 , G06T7/90 , G06T2207/10036 , G06T2207/10056 , G06T2207/10064 , G06T2207/20032 , G06T2207/20104 , G06T2207/20152 , G06T2207/30024 , G06T2207/30096
摘要： Methods, systems, and apparatuses for detecting and describing heterogeneity in a cell sample are disclosed herein. A plurality of fields of view (FOV) are generated for one or more areas of interest (AOI) within an image of the cell sample are generated. Hyperspectral or multispectral data from each FOV is organized into an image stack containing one or more z-layers, with each z-layer containing intensity data for a single marker at each pixel in the FOV. A cluster analysis is applied to the image stacks, wherein the clustering algorithm groups pixels having a similar ratio of detectable marker intensity across layers of the z-axis, thereby generating a plurality of clusters having similar expression patterns.
摘要翻译：本文公开了用于检测和描述细胞样品中的异质性的方法，系统和装置。生成针对单元样本的图像内的一个或多个感兴趣区域（AOI）的多个视野（FOV）。来自每个FOV的高光谱或多光谱数据被组织成包含一个或多个z层的图像堆叠，每个z层包含FOV中每个像素处的单个标记的强度数据。聚类分析被应用于图像堆叠，其中聚类算法对像素具有在z轴的层之间具有相似比率的可检测标记强度，从而生成具有相似表达模式的多个簇。

3. 发明申请

WO2019121564A2 COMPUTATIONAL PATHOLOGY APPROACH FOR RETROSPECTIVE ANALYSIS OF TISSUE-BASED COMPANION DIAGNOSTIC DRIVEN CLINICAL TRIAL STUDIES 审中-公开
公开(公告)号：WO2019121564A2
公开(公告)日：2019-06-27
申请号：PCT/EP2018/085308
申请日：2018-12-17
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , CHEFD'HOTEL, Christophe , CHUKKA, Srinivas
摘要： The present disclosure provides automated systems and methods for retrospectively analyzing clinical trial data.

4. 发明申请

WO2019110567A1 METHOD OF COMPUTING TUMOR SPATIAL AND INTER-MARKER HETEROGENEITY 审中-公开
公开(公告)号：WO2019110567A1
公开(公告)日：2019-06-13
申请号：PCT/EP2018/083444
申请日：2018-12-04
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , CHUKKA, Srinivas , SARKAR, Anindya
IPC分类号： G06T7/00 , G06T7/30 , G06T7/162
摘要： The present disclosure relates, among other things, to automated systems and methods for determining the variability between derived expression scores for a series of biomarkers between different identified cell clusters in a whole slide image. In some embodiments, the variability between derived expression scores may be a derived inter-marker heterogeneity metric.

5. 发明申请

WO2018065434A1 DIGITAL PATHOLOGY SYSTEM AND ASSOCIATED WORKFLOW FOR PROVIDING VISUALIZED WHOLE-SLIDE IMAGE ANALYSIS 审中-公开
标题翻译：数字病理学系统和相关的工作流程，用于提供可视化的整体幻灯片图像分析
公开(公告)号：WO2018065434A1
公开(公告)日：2018-04-12
申请号：PCT/EP2017/075113
申请日：2017-10-04
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , BREDNO, Joerg , CHUKKA, Srinivas , GUETTER, Christoph , LORSAKUL, Auranuch , SARKAR, Anindya , SUZUE, Ellen
IPC分类号： G06T7/00
摘要： A digital pathology system and associated method and computer program product provide a quantitative analysis of entire tissue slides as well as intuitive, effective, fast, and precise quantification of biomarker expressions across relevant areas of the entire tissue slides. The digital pathology system enables a novel workflow that allows the user to efficiently outline clinically relevant morphology in its entirety, including solid tumor areas. Quantitative analysis results are then efficiently and intuitively provided to the user for all tissue content (i.e., millions of cells) within seconds. This efficiency is made possible by a pre-computation step that computes and stores image analysis results for later retrieval. Visualizing vast amount of data effectively is another component of the system that provides information and confidence to the user about the biomarker expression levels.
摘要翻译：数字病理学系统和相关方法以及计算机程序产品提供对整个组织切片的定量分析以及对整个组织切片的相关区域的生物标记表达的直观，有效，快速和精确的量化。数字病理系统实现了一种新颖的工作流程，使用户能够有效地勾勒整个临床相关形态，包括实体肿瘤区域。然后在数秒内将定量分析结果有效且直观地提供给用户以获得所有组织含量（即，数百万个细胞）。通过计算和存储图像分析结果以供稍后检索的预计算步骤，可以提高效率。有效显示大量数据是该系统的另一个组成部分，为用户提供有关生物标志物表达水平的信息和信心。

6. 发明申请

WO2016034655A2 SYSTEMS AND METHODS FOR GENERATING FIELDS OF VIEW 审中-公开
标题翻译：用于生成视野的系统和方法
公开(公告)号：WO2016034655A2
公开(公告)日：2016-03-10
申请号：PCT/EP2015/070100
申请日：2015-09-03
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , CHEN, Ting , CHEFD'HOTEL, Christophe , TUBBS, Alisa , ASCIERTO, Paolo A.
IPC分类号： G06K9/00
CPC分类号： G06K9/00147 , G06K9/00127 , G06K9/00134 , G06K9/0014 , G06K9/52 , G06K2009/4666 , G06K2209/05 , G06T7/0012 , G06T7/11 , G06T2207/30024 , G06T2207/30088 , G06T2207/30096 , G06T2207/30242
摘要： Imaging systems, methods, and apparatuses for automatically identifying fields of view (FOVs) for regions in an image encompassing melanoma is disclosed. In embodiments and in further aspects of the present invention, a computer-implemented method is disclosed for a tumor region based immune score computation. The method, in accordance with the present invention, involves identifying regions, for example, tumor areas or regions around a tumor area, partitioning a whole slide image or portion of a whole slide image into multiple regions related to the tumor, selecting FOVs within each identified region, and computing a number of cells present in each FOV. An immune score and/or immune-related score is generated based on the cells counted in each FOV.
摘要翻译：公开了用于自动识别包含黑素瘤的图像中的区域的视场（FOV）的成像系统，方法和装置。在本发明的实施例和进一步的方面中，公开了一种用于基于肿瘤区域的免疫评分计算的计算机实现的方法。根据本发明的方法涉及识别区域，例如肿瘤区域或肿瘤区域周围的区域，将整个幻灯片图像或整个幻灯片图像的一部分划分成与肿瘤相关的多个区域，在每个区域内选择FOV 并且计算每个FOV中存在的多个单元。基于每个FOV中计数的细胞产生免疫评分和/或免疫相关评分。

7. 发明申请

WO2016016125A1 AUTOMATIC GLANDULAR AND TUBULE DETECTION IN HISTOLOGICAL GRADING OF BREAST CANCER 审中-公开
标题翻译：乳腺癌病理分级中的自动葡萄糖和血管检测
公开(公告)号：WO2016016125A1
公开(公告)日：2016-02-04
申请号：PCT/EP2015/067007
申请日：2015-07-24
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , CHUKKA, Srinivas , CHEFD´HOTEL, Christophe , NGUYEN, Kien
IPC分类号： G06K9/00
CPC分类号： G06K9/6227 , G06K9/00127 , G06K9/0014 , G06K9/00147 , G06K9/4647 , G06K9/6256 , G06K9/66 , G06T7/0012 , G06T7/11 , G06T7/13 , G06T7/40 , G06T2207/30024 , G06T2207/30068 , G06T2207/30096
摘要： Methods, systems, and apparatuses for automatically identifying glandular regions and tubule regions in a breast tissue sample are provided. An image of breast tissue is analyzed to detect nuclei and lumen candidates, identify tumor nuclei and true lumen from the candidates, and group tumor nuclei with neighboring tumor nuclei and lumina to define tubule glandular regions and non-tubule glandular regions of the image. Learnt supervised classifiers, such as random forest classifiers, can be applied to identify and classify the tumor nuclei and true lumina. Graph-cut methods can be applied to group the tumor nuclei and lumina and to define the tubule glandular regions and non-tubule glandular regions. The analysis can be applied to whole slide images and can resolve tubule areas with multiple layers of nuclei.
摘要翻译：提供了用于自动识别乳腺组织样品中的腺体区域和小管区域的方法，系统和装置。分析乳腺组织的图像以检测核和管腔候选物，从候选物中鉴定肿瘤细胞核和真腔，并将肿瘤细胞核与相邻的肿瘤细胞核和细胞核组合起来，以确定图像的小管腺体区域和非小管腺体区域。学习的监督分类器，如随机森林分类器，可用于识别和分类肿瘤细胞核和真实的水肿。图形方法可用于分组肿瘤细胞核和腔，并定义小管腺体区域和非小管腺体区域。分析可以应用于整张幻灯片图像，并可以解决具有多层核的小管区域。

8. 发明申请

WO2015189264A1 PREDICTING BREAST CANCER RECURRENCE DIRECTLY FROM IMAGE FEATURES COMPUTED FROM DIGITIZED IMMUNOHISTOPATHOLOGY TISSUE SLIDES 审中-公开
标题翻译：预测乳腺癌直接从数字化免疫组织化学组织滑动计算的图像特征恢复
公开(公告)号：WO2015189264A1
公开(公告)日：2015-12-17
申请号：PCT/EP2015/062930
申请日：2015-06-10
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG , LELAND STANFORD JUNIOR UNIVERSITY
发明人： CHUKKA, Srinivas , BARNES, Michael , KNOWLES, David
IPC分类号： G06T7/00 , G06K9/00 , C12Q1/68 , G01N21/64 , G06K9/62
CPC分类号： G06T7/0012 , C12Q1/6886 , G01N2021/6441 , G06K9/00147 , G06K9/6228 , G06K9/629 , G06T2207/10024 , G06T2207/10056 , G06T2207/10064 , G06T2207/20081 , G06T2207/30024 , G06T2207/30068 , G06T2207/30072 , G06T2207/30096
摘要： The subject disclosure presents systems and computer-implemented methods for assessing a risk of cancer recurrence in a patient based on a holistic integration of large amounts of prognostic information for said patient into a single comparative prognostic dataset. A risk classification system may be trained using the large amounts of information from a cohort of training slides from several patients, along with survival data for said patients. For example, a machine-learning-based binary classifier in the risk classification system may be trained using a set of granular image features computed from a plurality of slides corresponding to several cancer patients whose survival information is known and input into the system. The trained classifier may be used to classify image features from one or more test patients into a low-risk or high-risk group.
摘要翻译：该主题公开提供了基于将所述患者的大量预后信息整体整合到单个比较预后数据集中来评估患者中癌症复发风险的系统和计算机实现的方法。可以使用来自几名患者的训练幻灯片的队列中的大量信息以及所述患者的生存数据来训练风险分类系统。例如，风险分类系统中的基于机器学习的二进制分类器可以使用从对应于其生存信息已知并输入到系统的若干癌症患者的多个幻灯片计算的一组粒状图像特征进行训练。训练有素的分类器可用于将图像特征从一个或多个测试患者分类为低风险或高风险组。

9. 发明申请

WO2015124737A1 METHODS, KITS, AND SYSTEMS FOR SCORING THE IMMUNE RESPONSE TO CANCER BY SIMULTANEOUS DETECTION OF CD3, CD8, CD20 AND FOXP3 审中-公开
标题翻译：通过同时检测CD3，CD8，CD20和FOXP3来评估对癌症的免疫应答的方法，试剂盒和系统
公开(公告)号：WO2015124737A1
公开(公告)日：2015-08-27
申请号：PCT/EP2015/053643
申请日：2015-02-20
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： SEBASTIAO, Noemi , DAY, William , OCHS, Robert , CHUKKA, Srinivas , MARTIN, Jim , BARNES, Michael , BREDNO, Joerg , CHEN, Ting , TUBBS, Alisa , NIE, Yao
IPC分类号： G01N33/574
CPC分类号： G01N33/5743 , G01N15/1463 , G01N33/566 , G01N33/574 , G01N33/57415 , G01N33/6875 , G01N35/00029 , G01N2015/008 , G01N2015/1006 , G01N2015/1486 , G01N2035/00138 , G01N2333/4703 , G01N2333/4739 , G01N2333/4742 , G01N2333/70503 , G01N2333/7051 , G01N2333/70517 , G06F19/20
摘要： This disclosure describes methods, kits, and systems for scoring the immune response to cancer through examination of tissue infiltrating lymphocytes (TILs). Methods of scoring the immune response in cancer using tissue infiltrating lymphocytes include detecting CD3, CD8, CD20, and FoxP3 within the sample and scoring the detection manually or scoring the digital images of the staining with the aid of image analysis and algorithms.
摘要翻译：本公开描述了通过检查组织浸润淋巴细胞（TIL）评分对癌症的免疫应答的方法，试剂盒和系统。使用组织浸润淋巴细胞评估癌症免疫反应的方法包括检测样品中的CD3，CD8，CD20和FoxP3，手动评分检测，或借助图像分析和算法对染色的数字图像进行评分。

10. 发明申请

WO2017093524A1 DEVICES, SYSTEMS AND METHODS FOR AUTOMATED QUANTITATIVE SCORING OF DIGITIZED TISSUE IMAGES 审中-公开
标题翻译：用于数字化组织图像的自动定量评分的装置，系统和方法
公开(公告)号：WO2017093524A1
公开(公告)日：2017-06-08
申请号：PCT/EP2016/079655
申请日：2016-12-02
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： BARNES, Michael , BREDNO, Joerg , CHUKKA, Srinivas , SARKAR, Anindya , CHEFD'HOTEL, Christophe , NGUYEN, Kien
IPC分类号： G06T7/00 , G06T7/11 , G06T7/90
CPC分类号： G06T7/0012 , G06T7/11 , G06T7/90 , G06T2200/24 , G06T2207/10036 , G06T2207/10056 , G06T2207/10064 , G06T2207/20021 , G06T2207/20104 , G06T2207/30024 , G06T2207/30096
摘要： Methods and systems for generating a heat map that reduces bias in selecting FOVs are disclosed. Some disclosed methods include annotating a primary stained image, registering the annotation to a secondary serial specific stained image, using an image analysis algorithm to compute a scoring criteria specific to the tissue and assay type for tiled regions in the image, using a sliding window in the annotated tumor region to compute values for each pixel in a heat map which correlate to the specific scoring criteria, displaying the heat map at low resolution, ranking and selecting hot spots, selecting FOVs from the hot spot regions which results in displaying the slide-level score for the FOVs. The systems comprise, among other things, software configured to perform the referenced method.
摘要翻译：公开了用于生成减少选择FOV中的偏差的热图的方法和系统。一些公开的方法包括注释主要染色图像，将注释注册到次要系列特定染色图像，使用图像分析算法来计算特定于组织的评分标准以及图像中平铺区域的测定类型，使用滑动窗口注释的肿瘤区域以计算与特定评分标准相关的热图中的每个像素的值，以低分辨率显示热图，分级和选择热点，从热点区域选择FOV，这导致显示滑动 - 对于FOVs的评分。除其他外，系统包括配置为执行引用方法的软件。

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