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1. 发明申请

WO2019025533A1 AUTOMATIC ASSAY ASSESSMENT AND NORMALIZATION FOR IMAGE PROCESSING 审中-公开
公开(公告)号：WO2019025533A1
公开(公告)日：2019-02-07
申请号：PCT/EP2018/070978
申请日：2018-08-02
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： NIE, Yao , SAINZ DE CEA, Maria
IPC分类号： G16H30/40 , G06T7/00
摘要： Disclosed herein are systems and methods for normalizing the titer of a first stain to a titer of the same stain in a template image. Also disclosed are methods of assessing stain titer levels.

2. 发明申请

WO2019025520A1 COLOR UNMIXING WITH SCATTER CORRECTION 审中-公开
公开(公告)号：WO2019025520A1
公开(公告)日：2019-02-07
申请号：PCT/EP2018/070956
申请日：2018-08-02
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： NIE, Yao
IPC分类号： G06T5/00 , G06T7/90 , G06T7/00
摘要： The present disclosure provides systems and methods for separating colors in an image by automatically selecting color reference vectors that take into consideration the effect of light scattering, and principally how the light scattering changes the proportions of RGB channel signals in detected light at varying stain concentrations.

3. 发明申请

WO2016020391A2 IMAGE ANALYSIS SYSTEM USING CONTEXT FEATURES 审中-公开
标题翻译：使用上下文特征的图像分析系统
公开(公告)号：WO2016020391A2
公开(公告)日：2016-02-11
申请号：PCT/EP2015/067972
申请日：2015-08-04
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： CHUKKA, Srinivas , NIE, Yao
IPC分类号： G06K9/00
CPC分类号： G06K9/00147 , G06K9/6269 , G06K9/627 , G06K9/6277 , G06K9/6292 , G06K2209/05
摘要： The present disclosure relates to an image analysis system for identifying objects belonging to a particular objet class in a digital image (102-108) of a biological sample, the system comprising a processor and memory, the memory comprising interpretable instructions which, when executed by the processor, cause the processor to perform a method comprising: - analyzing (602) the digital image for automatically or semi-automatically identifying objects in the digital image; - analyzing (604) the digital image for identifying, for each object, a first object feature value (202, 702) of a first object feature of said object; - analyzing (606) the digital image for computing one or more first context feature values (204, 704), each first context feature value being a derivative of the first object feature values or of other object feature values of a plurality of the objects in the digital image or being a derivative of a plurality of pixels of the digital image; - inputting (608) both the first object feature value of each of the objects in the digital image and the first context feature value of said digital image into a first classifier (210, 710); and - executing (610) the first classifier, the first classifier thereby using the first object feature value of each object and the one or more first context feature values as input for automatically determining, for said object, a first likelihood (216, 714) of said object of being a member of the object class.
摘要翻译：本公开涉及一种用于识别属于生物样本的数字图像（102-108）中的特定对象类的对象的图像分析系统，所述系统包括处理器和存储器，所述存储器包括可解释的指令，所述可解释的指令在由所述处理器执行时使所述处理器执行包括以下的方法： - 分析（602）所述数字图像以自动或半自动地识别所述数字图像中的物体; - 分析（604）数字图像，用于针对每个对象识别所述对象的第一对象特征的第一对象特征值（202,702）; - - 分析（606）用于计算一个或多个第一上下文特征值（204,704）的数字图像，每个第一上下文特征值是第一对象特征值或多个对象中的对象的特征值的导数数字图像或者是数字图像的多个像素的导数; - 将数字图像中的每个对象的第一对象特征值和所述数字图像的第一上下文特征值输入（608）到第一分类器（210,710）中; 以及 - 执行（610）所述第一分类器，所述第一分类器由此使用每个对象的所述第一对象特征值和所述一个或多个第一上下文特征值作为输入以用于针对所述对象自动确定第一似然性（216,714）所述对象是对象类的成员。

4. 发明申请

WO2018083142A1 SYSTEMS AND METHODS FOR ENCODING IMAGE FEATURES OF HIGH-RESOLUTION DIGITAL IMAGES OF BIOLOGICAL SPECIMENS 审中-公开
标题翻译：用于编码生物样本的高分辨率数字图像的图像特征的系统和方法
公开(公告)号：WO2018083142A1
公开(公告)日：2018-05-11
申请号：PCT/EP2017/077999
申请日：2017-11-02
申请人： VENTANA MEDICAL SYSTEMS, INC. , F. HOFFMANN-LA ROCHE AG
发明人： NIE, Yao
IPC分类号： G06K9/00
摘要： An image analysis system for analyzing biological specimen images is disclosed. The system may include: a superpixel generator configured to obtain a biological specimen image and group pixels of the biological specimen image into a plurality of superpixels; a feature extractor configured to extract, from each superpixel in the plurality of superpixels, a feature vector comprising a plurality of image features; a clustering engine configured to assign the plurality of superpixels to a predefined number of clusters, each cluster being characterized by a centroid vector of feature vectors of superpixels assigned to the cluster; and a storage interface configured to store, for each superpixel in the plurality of superpixels, clustering information identifying the one cluster to which the superpixel is assigned. The system may also include a graph engine configured construct a graph based on the stored information, and use the graph to perform a graph-based image processing task.
摘要翻译：公开了一种用于分析生物标本图像的图像分析系统。该系统可以包括：超像素生成器，配置为获得生物样本图像并将生物样本图像的像素分组为多个超像素; 特征提取器，被配置为从所述多个超像素中的每个超像素提取包括多个图像特征的特征向量; 聚类引擎，其被配置为将所述多个超像素分配给预定义数量的聚类，每个聚类的特征在于分配给所述聚类的超级像素的特征矢量的质心矢量; 以及存储接口，被配置为针对所述多个超像素中的每个超像素存储标识所述超像素被分配到的一个簇的聚类信息。该系统还可以包括图形引擎，该图形引擎被配置为基于所存储的信息来构建图形，并且使用该图形来执行基于图形的图像处理任务。

5. 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。

6. 发明申请

WO2020081343A1 SYSTEMS AND METHODS FOR CELL CLASSIFICATION 审中-公开
公开(公告)号：WO2020081343A1
公开(公告)日：2020-04-23
申请号：PCT/US2019/055558
申请日：2019-10-10
申请人： VENTANA MEDICAL SYSTEMS, INC.
发明人： NIE, Yao , YOUSEFI, Safoora
IPC分类号： G06K9/00 , G06K9/62 , G06K9/46
摘要： The present disclosure relates to automated systems and methods adapted to quickly and accurately train a neural network to detect and/or classify cells and/or nuclei. The present disclosure also relates to automated systems and methods for using a trained cell detection and classification engine, such as one including a neural network, to classify cells within an unlabeled image.

7. 发明申请

WO2023043709A1 MACHINE-LEARNING TECHNIQUES FOR PREDICTING PHENOTYPES IN DUPLEX DIGITAL PATHOLOGY IMAGES 审中-公开
公开(公告)号：WO2023043709A1
公开(公告)日：2023-03-23
申请号：PCT/US2022/043285
申请日：2022-09-13
申请人： VENTANA MEDICAL SYSTEMS, INC.
发明人： MARTIN, Jim F. , NIE, Yao , VENUGOPAL, Raghavan , WANG, Xingwei
IPC分类号： G06V20/69 , G06V10/80 , G06V10/82
摘要： Duplex immunohistochemistry (IHC) staining of tissue sections allows simultaneous detection of two biomarkers and their co-expression at the single-cell level, and does not require two IHC stains and additional registration to identify co-localization. Duplex IHC are often difficult for human including pathologists to reliably score. The methods and system herein use machine-learning models and probability maps to detect and record individual phenotype ER/PR.

8. 发明申请

WO2022265883A1 DIGITAL SYNTHESIS OF HISTOLOGICAL STAINS USING MULTIPLEXED IMMUNOFLUORESCENCE IMAGING 审中-公开
公开(公告)号：WO2022265883A1
公开(公告)日：2022-12-22
申请号：PCT/US2022/032468
申请日：2022-06-07
申请人： VENTANA MEDICAL SYSTEMS, INC.
发明人： WANG, Xingwei , ZHAO, Zuo , LORSAKUL, Auranuch , NIE, Yao
IPC分类号： G06T11/00
摘要： Techniques for obtaining a synthetic histochemically stained image from a multiplexed immunofluorescence (MPX) image may include producing an N-channel input image that is based on information from each of M channels of an MPX image of a tissue section, where M and N are positive integers and N is less than or equal to M; and generating a synthetic image by processing the N-channel input image using a generator network, the generator network having been trained using a training data set that includes a plurality of pairs of images. The synthetic image depicts a tissue section stained with at least one histochemical stain. Each pair of images of the plurality of pairs of images includes an N-channel image, produced from an MPX image of a first section of a tissue, and an image of a second section of the tissue stained with the at least one histochemical stain.

9. 发明申请

WO2022221572A1 TRANSFORMATION OF HISTOCHEMICALLY STAINED IMAGES INTO SYNTHETIC IMMUNOHISTOCHEMISTRY (IHC) IMAGES 审中-公开
公开(公告)号：WO2022221572A1
公开(公告)日：2022-10-20
申请号：PCT/US2022/024879
申请日：2022-04-14
申请人： VENTANA MEDICAL SYSTEMS, INC. , GENENTECH, INC.
发明人： WANG, Xingwei , LORSAKUL, Auranuch , ZHAO, Zuo , NIE, Yao , KOEPPEN, Hartmut , KOLSTER, Hauke , SHANMUGAM, Kandavel
IPC分类号： G06T1/00 , G06T7/10 , G01N1/30 , G06T11/00
摘要： The present disclosure relates to techniques for obtaining a synthetic immunohistochemistry (IHC) image from a histochemically stained image. Particularly, aspects of the present disclosure are directed to accessing an input image that depicts a tissue section that has been stained with at least one histochemical stain; generating a synthetic image by processing the input image using a trained generator network; and outputting the synthetic image. The synthetic image depicts a tissue section that has been stained with at least one IHC stain that targets a first antigen, and techniques may also include receiving an input that is based on a level of expression of a first antigen from the synthetic image and/or generating, from the synthetic image, a value that is based on a level of expression of the first antigen.

10. 发明申请

WO2022046463A1 HISTOLOGICAL STAIN PATTERN AND ARTIFACTS CLASSIFICATION USING FEW-SHOT LEARNING 审中-公开
公开(公告)号：WO2022046463A1
公开(公告)日：2022-03-03
申请号：PCT/US2021/046242
申请日：2021-08-17
申请人： VENTANA MEDICAL SYSTEMS, INC.
发明人： ROESSLER, Christian , NIE, Yao , SHAIKH, Nazim , BAUER, Daniel
IPC分类号： G06K9/00
摘要： A method and system for classifying field of view (FOV) images of histological slides into various categories that include certain stain patterns, artifacts, and/or other features of interest are provided herein. Few-shot learning (e.g., a prototypical network) techniques are used to train a deep convolutional neural network using a small number of training samples for a small number of image classes for classifying stain images belonging to a larger number of image classes.

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