公开(公告)号：US12131464B2

公开(公告)日：2024-10-29

申请号：US17623090

申请日：2020-06-26

申请人： Visiopharm A/S

发明人： Michael Grunkin ,  Johan Doré Hansen ,  Jeppe Thagaard

IPC分类号： G06N20/00 ,  G02B21/34 ,  G02B21/36 ,  G06T7/00 ,  G06V20/69

CPC分类号： G06T7/0012 ,  G02B21/34 ,  G02B21/367 ,  G06V20/695 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024

摘要： A method of analyzing a plurality of histology slides is provided, wherein possible artefacts are detected at an early stage. This is achieved by including a preliminary imaging and image analysis step in the process flow; the step being executed preferably before any diagnostic assessment e.g. image analysis or manual reading is performed by a pathologist or a lab technician. Accordingly, the histology slides reaching the expert for image analysis are of a higher quality, since the slides are ideally free of artefacts. The method thus saves valuable time for the pathologist, since only artefact-free slides will be subject to a detailed analysis. Furthermore, the method minimizes the risk of misinterpretations leading to potentially false diagnoses. A deep learning model, is also disclosed, which is capable of automatically determining whether histopathological images are suitable for diagnostic and/or research assessment. A training of the deep learning model is also disclosed.

公开(公告)号：US12125560B2

公开(公告)日：2024-10-22

申请号：US18078803

申请日：2022-12-09

申请人： FenoLogica Biosciences, Inc.

发明人： Matthew Ian Wright ,  Adrian Christopher Scott ,  Sean Matthew MacLeod ,  Megan Lew Kuhn

IPC分类号： G16B40/30 ,  C12M1/36 ,  G01N15/10 ,  G01N15/1429 ,  G01N15/1433 ,  G06V20/69 ,  G16B45/00 ,  G16H10/40 ,  G16H30/40

CPC分类号： G16B40/30 ,  C12M41/48 ,  G06V20/695 ,  G06V20/698 ,  G16B45/00 ,  G16H10/40 ,  G01N2015/1006 ,  G01N15/1429 ,  G01N15/1433 ,  G16H30/40

摘要： An image acquisition and analysis system are disclosed. The system enables high throughput, objective analysis of microbial samples over days or weeks. The system may accommodate upwards of twelve 96- or 384-well plates simultaneously (liquid or solid media). The system may acquire and analyze a large number of samples in a short period of time. For example, over 384 samples per minute or 18,432 samples per hour. The system hardware may include a multi-spectral imager (fluorescence and bright field detection), electro-mechanical assemblies, and an optional high-resolution stage. The system may automate image acquisition, image data processing, simplify data storage, and enable automated analysis tools to significantly reduce the manual labor and time associated with such tasks. The system may allow for quick processing and analysis of data into clear phenotypic classes. The analysis capabilities may include colony growth, colorimetry, and structural morphology assays, and automated phenotype classification capabilities.

公开(公告)号：US12118721B2

公开(公告)日：2024-10-15

申请号：US18100543

申请日：2023-01-23

申请人： Owkin Inc. ,  Owkin France SAS

发明人： Pierre Courtiol ,  Olivier Moindrot ,  Charles Maussion ,  Charlie Saillard ,  Benoit Schmauch ,  Gilles Wainrib

IPC分类号： G06T7/00 ,  G06F18/21 ,  G06F18/214 ,  G06F18/23 ,  G06F18/2413 ,  G06N3/04 ,  G06T7/11 ,  G06T7/194 ,  G06V10/32 ,  G06V10/50 ,  G06V10/764 ,  G06V10/82 ,  G06V20/69

CPC分类号： G06T7/0012 ,  G06F18/214 ,  G06F18/2163 ,  G06F18/217 ,  G06F18/23 ,  G06F18/2413 ,  G06N3/04 ,  G06T7/11 ,  G06T7/194 ,  G06V10/32 ,  G06V10/50 ,  G06V10/764 ,  G06V10/82 ,  G06V20/695 ,  G06V20/698 ,  G06T2207/10056 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024

摘要： A method and apparatus of a device that classifies an image is described. In an exemplary embodiment, the device segments the image into a region of interest that includes information useful for classification and a background region by applying a first convolutional neural network. In addition, the device tiles the region of interest into a set of tiles. For each tile, the device extracts a feature vector of that tile by applying a second convolutional neural network, where the features of the feature vectors represent local descriptors of the tile. Furthermore, the device processes the extracted feature vectors of the set of tiles to classify the image.

公开(公告)号：US20240304007A1

公开(公告)日：2024-09-12

申请号：US18614717

申请日：2024-03-24

申请人： WUXI NO. 2 PEOPLE'S HOSPITAL

发明人： NINGHAN FENG ,  HONG TANG ,  GUANZHEN YU ,  YUEZHOU ZHANG ,  YANGKUN FENG ,  FENGPING LIU ,  YANG WANG ,  PENG JIANG

IPC分类号： G06V20/69 ,  G06T7/00 ,  G06T7/11 ,  G06V10/44 ,  G06V10/46 ,  G06V10/762 ,  G16H30/40 ,  H04N1/40

CPC分类号： G06V20/695 ,  G06T7/0012 ,  G06T7/11 ,  G06V10/44 ,  G06V10/46 ,  G06V10/762 ,  G16H30/40 ,  H04N1/40012 ,  G06T2207/30024

摘要： This invention discloses a method and system for the segmentation and clustering of nuclei based on single-cell pathological images. The contour tracing method is used to calculate all the closed contours existing in the pathological tissue images; and optimizes the contours to obtain the segmented images of the nuclei. Then, according to the mask image corresponding to the segmented images of the nuclei, the segmented images of the nuclei are divided into individual nucleus images; the influencing features of the nuclei in the corresponding area are extracted through the mask image; through feature selection, redundant features are removed, and then the UMAP feature reduction method is used to select the two most important features for clustering the nuclei. By first segmenting and dividing the nucleus area in the pathological images, and then using the divided single nucleus for feature extraction, the basis for clustering is made more objective.

公开(公告)号：US20240290117A1

公开(公告)日：2024-08-29

申请号：US18586622

申请日：2024-02-26

申请人： LEICA MICROSYSTEMS CMS GMBH

发明人： Luis ALVAREZ ,  Frank HECHT ,  Julia ROBERTI ,  Giulia OSSATO

IPC分类号： G06V20/69 ,  G01N21/64 ,  G06V10/25

CPC分类号： G06V20/698 ,  G01N21/6408 ,  G01N21/6458 ,  G06V10/25 ,  G06V20/693 ,  G06V20/695

摘要： A processor for lifetime-based unmixing in fluorescence microscopy is configured to acquire an image having a plurality of pixels, each pixel providing information on photon count and photon arrival times, generate a phasor plot that is a vector space representation of the image, partition the image into image segments, evaluate the image segments according to total photon counts of the corresponding subsets of pixels, and execute a lifetime classification by selecting an image segment having a largest total photon count, determining a region of interest in the image encompassing the image segment, determining a phasor subset in the phasor plot corresponding to the region of interest, and generating a lifetime class including a set of image segments corresponding to the phasor subset. A plurality of lifetime classes is generated by iteratively executing the lifetime classification. The processor is configured to perform lifetime-based unmixing using the life-time classes.

公开(公告)号：US20240290116A1

公开(公告)日：2024-08-29

申请号：US18572629

申请日：2022-03-25

申请人： HORIBA, LTD.

发明人： Yasuhiro TATEWAKI

IPC分类号： G06V20/69 ,  G01N15/0205 ,  G06V10/98

CPC分类号： G06V20/698 ,  G01N15/0211 ,  G06V10/993 ,  G06V20/695

摘要： A particle analysis apparatus includes: an individual particle image generation unit that extracts individual particles from the original image and generates individual particle images; a particle characteristic calculation unit that calculates one or a plurality of types of particle characteristics for a particle in each of the individual particle images, based on the each of the individual particle images; a classification unit that classifies, with respect to a plurality of classes defined by some or all of the one or plurality of types of particle characteristics, the particles into the classes that correspond to the calculated one or plurality of particle characteristics; and an individual particle image storing unit that stores in a storage the individual particle images of particles belonging to each of the plurality of classes.

公开(公告)号：US12067793B2

公开(公告)日：2024-08-20

申请号：US17235888

申请日：2021-04-20

申请人： Mohd Amin Abu Qura

发明人： Mohd Amin Abu Qura

IPC分类号： G06T7/00 ,  G01S17/89 ,  G06K9/00 ,  G06K9/46 ,  G06V20/69

CPC分类号： G06V20/69 ,  G01S17/89 ,  G06T7/0014 ,  G06V20/693 ,  G06V20/695 ,  G06T2207/10028 ,  G06V2201/03

摘要： An Enterobius vermicularis detection system is provided comprising a sample substrate, a sample disposed upon the sample substrate, and a personal computing device comprising an imaging device for acquiring one or more digital images of the sample substrate. The personal computing device may operate a digital interface allowing the acquired one or more digital images to be uploaded to one or more analysis computation servers. The one or more analysis computation servers may execute an analysis process upon the uploaded one or more digital images allowing determination of a presence of one or more Enterobius vermicularis eggs within the sample. The analysis process may output a first confidence interval value representing a likelihood of the presence of one or more Enterobius vermicularis eggs within the sample. The one or more analysis computation servers may communicate the first confidence interval value to the personal electronic device.

公开(公告)号：US20240273927A1

公开(公告)日：2024-08-15

申请号：US18642080

申请日：2024-04-22

申请人： PAIGE.AI, Inc.

发明人： Brandon ROTHROCK ,  Christopher KANAN ,  Julian VIRET ,  Thomas FUCHS ,  Leo GRADY

IPC分类号： G06V20/69 ,  G06F18/214 ,  G06N20/00 ,  G06T7/00 ,  G06T7/136 ,  G06T7/194 ,  G06V10/26 ,  G06V10/28

CPC分类号： G06V20/695 ,  G06F18/2155 ,  G06N20/00 ,  G06T7/0012 ,  G06T7/136 ,  G06T7/194 ,  G06V10/26 ,  G06V10/28 ,  G06V20/698 ,  G06T2207/20081 ,  G06T2207/30024

摘要： Systems and methods are disclosed for receiving one or more electronic slide images associated with a tissue specimen, the tissue specimen being associated with a patient and/or medical case, partitioning a first slide image of the one or more electronic slide images into a plurality of tiles, detecting a plurality of tissue regions of the first slide image and/or plurality of tiles to generate a tissue mask, determining whether any of the plurality of tiles corresponds to non-tissue, removing any of the plurality of tiles that are determined to be non-tissue, determining a prediction, using a machine learning prediction model, for at least one label for the one or more electronic slide images, the machine learning prediction model having been generated by processing a plurality of training images, and outputting the prediction of the trained machine learning prediction model.

公开(公告)号：US20240265532A1

公开(公告)日：2024-08-08

申请号：US18556411

申请日：2022-04-19

申请人： Biocellvia

发明人： Cindy SERDJEBI ,  Damien BARBES ,  Bastien LEPOIVRE ,  Karine BERTOTTI

IPC分类号： G06T7/00 ,  G06T7/62 ,  G06V20/69

CPC分类号： G06T7/0012 ,  G06T7/62 ,  G06V20/695 ,  G06T2207/10024 ,  G06T2207/20036 ,  G06T2207/30024 ,  G06T2207/30096 ,  G06T2207/30101

摘要： The invention relates to a method for producing a morphometric quantity of interest for a section of a human or animal organ on the basis of a first digital representation of a histological slide that has been subjected to a staining step that causes the pixels of said first digital representation to become different colours depending on whether said pixels describe emptiness, tissue or muscle cells. Said method especially consists in identifying pixels describing at least one polygon of interest in digital representations created from the first digital representation, in discerning, per polygon of interest, a lumen, an intima and a media of a vessel, and in producing at least one morphometric measurement of said vessel. Such a method comprises a step of producing a morphometric quantity of interest for the organ on the basis of said morphometric measurements of the identified vessels.

公开(公告)号：US12056211B2

公开(公告)日：2024-08-06

申请号：US17501899

申请日：2021-10-14

申请人： TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED

发明人： Yifan Hu ,  Yuexiang Li ,  Yefeng Zheng

IPC分类号： G06V20/70 ,  A61B6/00 ,  G06F18/21 ,  G06F18/214 ,  G06N3/0455 ,  G06T7/10 ,  G06T7/143 ,  G06T9/00 ,  G06V20/69

CPC分类号： G06F18/2155 ,  A61B6/5294 ,  G06F18/2178 ,  G06N3/0455 ,  G06T7/10 ,  G06T7/143 ,  G06T9/002 ,  G06V20/695 ,  G06V20/70 ,  G06T2207/20112 ,  G06T2207/30004 ,  G06T2219/004

摘要： A method for determining a target image to be labeled includes: obtaining an original image and an autoencoder (AE) set, the original image being an image having not been labeled, the AE set including N AEs; obtaining an encoded image set corresponding to the original image by using the AE set, the encoded image set including N encoded images, the encoded images being corresponding to the AEs; obtaining the encoded image set and a segmentation result set corresponding to the original image by using an image segmentation network, the image segmentation network including M image segmentation sub-networks, and the segmentation result set including [(N+1)*M] segmentation results; determining labeling uncertainty corresponding to the original image according to the segmentation result set; and determining whether the original image is a target image according to the labeling uncertainty.