Patents by Inventor Christophe Chefd?hotel

Christophe Chefd?hotel has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 10664967
    Abstract: 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.
    Type: Grant
    Filed: May 26, 2017
    Date of Patent: May 26, 2020
    Assignees: VENTANA MEDICAL SYSTEMS, INC., OREGON HELATH & SCIENCE UNIVERSITY
    Inventors: Michael Barnes, David Chafin, Karl Garsha, Thomas M. Grogan, Esteban Roberts, Benjamin Stevens, Franklin Ventura, Christophe Chefd'hotel, Kandavel Shanmugam, Joe Gray, Damien Ramunno-Johnson, Tania Vu, Brian J. Druker, Thomas Jacob
  • Publication number: 20200143542
    Abstract: 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.
    Type: Application
    Filed: December 21, 2019
    Publication date: May 7, 2020
    Applicants: Ventana Medical Systems, Inc., Providence Health & Services - Oregon
    Inventors: Michael Barnes, Carlo Bifulco, Christophe Chefd'hotel, Ting Chen, Alisa Tubbs
  • Patent number: 10628658
    Abstract: Disclosed, among other things, is a computer device and computer-implemented method of classifying cells within an image of a tissue sample comprising providing the image of the tissue sample as input; computing nuclear feature metrics from features of nuclei within the image; computing contextual information metrics based on nuclei of interest with the image; classifying the cells within the image using a combination of the nuclear feature metrics and contextual information metrics.
    Type: Grant
    Filed: May 10, 2017
    Date of Patent: April 21, 2020
    Assignee: Ventana Medical Systems, Inc.
    Inventors: Joerg Bredno, Christophe Chefd'hotel, Kien Nguyen
  • Publication number: 20200090330
    Abstract: The subject disclosure presents systems and computer-implemented methods for automatic immune cell detection that is of assistance in clinical immune profile studies. The automatic immune cell detection method involves retrieving a plurality of image channels from a multi-channel image such as an RGB image or biologically meaningful unmixed image. A cell detector is trained to identify the immune cells by a convolutional neural network in one or multiple image channels. Further, the automatic immune cell detection algorithm involves utilizing a non-maximum suppression algorithm to obtain the immune cell coordinates from a probability map of immune cell presence possibility generated from the convolutional neural network classifier.
    Type: Application
    Filed: November 19, 2019
    Publication date: March 19, 2020
    Applicant: Ventana Medical Systems, Inc.
    Inventors: Christophe Chefd'hotel, Ting Chen
  • Patent number: 10552960
    Abstract: 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.
    Type: Grant
    Filed: March 2, 2018
    Date of Patent: February 4, 2020
    Assignees: Ventana Medical Systems, Inc., Providence Health & Services—Oregon
    Inventors: Michael Barnes, Carlo Bifulco, Christophe Chefd'hotel, Ting Chen, Alisa Tubbs
  • Patent number: 10540771
    Abstract: An image segmentation method is disclosed that allows a user to select image component types, for example tissue types and or background, and have the method of the present invention segment the image according to the user's input utilizing the superpixel image feature data and spatial relationships.
    Type: Grant
    Filed: September 20, 2017
    Date of Patent: January 21, 2020
    Assignee: Ventana Medical Systems, Inc.
    Inventors: Christophe Chefd'hotel, Stanley Ho, Yao Nie
  • Patent number: 10529072
    Abstract: The subject disclosure presents systems and computer-implemented methods for automatic immune cell detection that is of assistance in clinical immune profile studies. The automatic immune cell detection method involves retrieving a plurality of image channels from a multi-channel image such as an RGB image or biologically meaningful unmixed image. A cell detector is trained to identify the immune cells by a convolutional neural network in one or multiple image channels. Further, the automatic immune cell detection algorithm involves utilizing a non-maximum suppression algorithm to obtain the immune cell coordinates from a probability map of immune cell presence possibility generated from the convolutional neural network classifier.
    Type: Grant
    Filed: September 13, 2018
    Date of Patent: January 7, 2020
    Assignee: Ventana Medical Systems, Inc.
    Inventors: Christophe Chefd'hotel, Ting Chen
  • Publication number: 20190376878
    Abstract: The subject disclosure presents systems and methods for improved meso-dissection of biological specimens and tissue slides including importing one or more reference slides with annotations, using inter-marker registration algorithms to automatically map the annotations to an image of a milling slide, and dissecting the annotated tissue from the selected regions in the milling slide for analysis, while concurrently tracking the data and analysis using unique identifiers such as bar codes.
    Type: Application
    Filed: August 26, 2019
    Publication date: December 12, 2019
    Inventors: Michael Barnes, Christophe Chefd'hotel, Srinivas Chukka, Mohammad Qadri
  • Patent number: 10445619
    Abstract: 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.
    Type: Grant
    Filed: January 27, 2017
    Date of Patent: October 15, 2019
    Assignee: Ventana Medical Systems, Inc.
    Inventors: Michael Barnes, Christophe Chefd'hotel, Srinivas Chukka, Kien Nguyen
  • Publication number: 20190038310
    Abstract: A method of segmenting images of biological specimens using adaptive classification to segment a biological specimen into different types of tissue regions. The segmentation is performed by, first, extracting features from the neighborhood of a grid of points (GPs) sampled on the whole-slide (WS) image and classifying them into different tissue types. Secondly, an adaptive classification procedure is performed where some or all of the GPs in a WS image are classified using a pre-built training database, and classification confidence scores for the GPs are generated. The classified GPs with high confidence scores are utilized to generate an adaptive training database, which is then used to re-classify the low confidence GPs. The motivation of the method is that the strong variation of tissue appearance makes the classification problem more challenging, while good classification results are obtained when the training and test data origin from the same slide.
    Type: Application
    Filed: September 13, 2018
    Publication date: February 7, 2019
    Inventors: Joerg Bredno, Christophe Chefd'hotel, Ting Chen, Srinivas Chukka, Kien Nguyen
  • Publication number: 20190012787
    Abstract: The subject disclosure presents systems and computer-implemented methods for automatic immune cell detection that is of assistance in clinical immune profile studies. The automatic immune cell detection method involves retrieving a plurality of image channels from a multi-channel image such as an RGB image or biologically meaningful unmixed image. A cell detector is trained to identify the immune cells by a convolutional neural network in one or multiple image channels. Further, the automatic immune cell detection algorithm involves utilizing a non-maximum suppression algorithm to obtain the immune cell coordinates from a probability map of immune cell presence possibility generated from the convolutional neural network classifier.
    Type: Application
    Filed: September 13, 2018
    Publication date: January 10, 2019
    Inventors: Christophe Chefd'hotel, Ting Chen
  • Patent number: 10127675
    Abstract: Systems and methods for generating a locally adaptive threshold image for foreground detection performing operations including creating a saliency edge strength image or layer indicating edge or border pixels of the nuclei by performing tensor voting on pixels neighboring the initial edge pixels within an image region to refine true edges are featured. Further, for each of a plurality of regions or blocks of the image, an adaptive threshold image is determined by sampling a foreground pixel and a background pixel for each initial edge pixel or refined edge pixel, generating histograms for both background and foreground saliency (or gradient magnitude) modulated histograms, determining a threshold range for each block of the image, and interpolating the threshold at each pixel based on the threshold range at each block. Comparing the input image with the resulting locally adaptive threshold image enables extraction of significantly improved foreground.
    Type: Grant
    Filed: December 21, 2016
    Date of Patent: November 13, 2018
    Assignee: Ventana Medical Systems, Inc.
    Inventors: Christophe Chefd'hotel, Srinivas Chukka, Xiuzhong Wang
  • Patent number: 10127433
    Abstract: Embodiments disclosed herein are directed, among other things, to imaging systems, methods, and apparatuses for automatically identifying fields of view (FOVs) for regions in an image encompassing tumor are 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 may be generated based on the cells counted in each FOV.
    Type: Grant
    Filed: March 2, 2017
    Date of Patent: November 13, 2018
    Assignee: VENTANA MEDICAL SYSTEMS, INC.
    Inventors: Paolo Ascierto, Michael Barnes, Christophe Chefd'hotel, Ting Chen, Alisa Tubbs
  • Publication number: 20180322632
    Abstract: 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.
    Type: Application
    Filed: March 2, 2018
    Publication date: November 8, 2018
    Inventors: Michael Barnes, Carlo Bifulco, Christophe Chefd'hotel, Ting Chen, Alisa Tubbs
  • Patent number: 10109052
    Abstract: The subject disclosure presents systems and computer-implemented methods for automatic immune cell detection that is of assistance in clinical immune profile studies. The automatic immune cell detection method involves retrieving a plurality of image channels from a multi-channel image such as an RGB image or biologically meaningful unmixed image. A cell detector is trained to identify the immune cells by a convolutional neural network in one or multiple image channels. Further, the automatic immune cell detection algorithm involves utilizing a non-maximum suppression algorithm to obtain the immune cell coordinates from a probability map of immune cell presence possibility generated from the convolutional neural network classifier.
    Type: Grant
    Filed: November 23, 2016
    Date of Patent: October 23, 2018
    Assignee: VENTANA MEDICAL SYSTEMS, INC.
    Inventors: Christophe Chefd'hotel, Ting Chen
  • Patent number: 10102418
    Abstract: A method of segmenting images of biological specimens using adaptive classification to segment a biological specimen into different types of tissue regions. The segmentation is performed by, first, extracting features from the neighborhood of a grid of points (GPs) sampled on the whole-slide (WS) image and classifying them into different tissue types. Secondly, an adaptive classification procedure is performed where some or all of the GPs in a WS image are classified using a pre-built training database, and classification confidence scores for the GPs are generated. The classified GPs with high confidence scores are utilized to generate an adaptive training database, which is then used to re-classify the low confidence GPs. The motivation of the method is that the strong variation of tissue appearance makes the classification problem more challenging, while good classification results are obtained when the training and test data origin from the same slide.
    Type: Grant
    Filed: July 28, 2016
    Date of Patent: October 16, 2018
    Assignee: VENTANA MEDICAL SYSTEMS, INC.
    Inventors: Joerg Bredno, Christophe Chefd'hotel, Ting Chen, Srinivas Chukka, Kien Nguyen
  • Publication number: 20180204048
    Abstract: Systems and methods discussed herein include, among other things, a method comprising quantifying analyte staining of a biological compartment in a region in which said staining is intermixed with analyte staining of an analytically-distinct distinct biological compartment. Disclosed systems and methods include, for example, a system and method for identifying membrane staining of an analyte of interest in regions where diffuse membrane staining is intermixed with cytoplasmic staining and/or punctate staining is disclosed. Disclosed systems and methods include, for example, a system and method for quantifying membrane staining of an analyte of interest in tissue or cytological samples having regions in which membrane staining is intermixed with cytoplasmic staining and/or punctate staining.
    Type: Application
    Filed: March 2, 2018
    Publication date: July 19, 2018
    Inventors: Christophe Chefd'hotel, Kien Nguyen
  • Publication number: 20180012365
    Abstract: An image segmentation method is disclosed that allows a user to select image component types, for example tissue types and or background, and have the method of the present invention segment the image according to the user's input utilizing the superpixel image feature data and spatial relationships.
    Type: Application
    Filed: September 20, 2017
    Publication date: January 11, 2018
    Inventors: Christophe Chefd'hotel, Stanley Ho, Yao Nie
  • Publication number: 20170372117
    Abstract: Disclosed, among other things, is a computer device and computer-implemented method of classifying cells within an image of a tissue sample comprising providing the image of the tissue sample as input; computing nuclear feature metrics from features of nuclei within the image; computing contextual information metrics based on nuclei of interest with the image; classifying the cells within the image using a combination of the nuclear feature metrics and contextual information metrics.
    Type: Application
    Filed: May 10, 2017
    Publication date: December 28, 2017
    Inventors: Joerg Bredno, Christophe Chefd'hotel, Kien Nguyen
  • Publication number: 20170328817
    Abstract: The subject disclosure presents systems and methods for improved meso-dissection of biological specimens and tissue slides including importing one or more reference slides with annotations, using inter-marker registration algorithms to automatically map the annotations to an image of a milling slide, and dissecting the annotated tissue from the selected regions in the milling slide for analysis, while concurrently tracking the data and analysis using unique identifiers such as bar codes.
    Type: Application
    Filed: July 28, 2017
    Publication date: November 16, 2017
    Inventors: Michael Barnes, Christophe Chefd'hotel, Srinivas Chukka, Mohammad Qadri