公开(公告)号：US12082770B2

公开(公告)日：2024-09-10

申请号：US17277158

申请日：2019-08-16

申请人： NEC Corporation

发明人： Masahiro Saikou

IPC分类号： G06T7/73 ,  A61B1/00 ,  A61B1/31 ,  G06T7/00 ,  G06T7/50

CPC分类号： A61B1/000094 ,  A61B1/00045 ,  A61B1/31 ,  G06T7/0012 ,  G06T7/50 ,  G06T7/74 ,  G06T2207/30028

摘要： A location estimation apparatus 1 includes: a feature amount extraction unit 2 configured to extract, a feature amount of a living-body internal image, from the living-body internal image captured using an endoscope; a similarity degree output unit 3 configured to output similarity degrees with a plurality of locations inside a living body using the feature amount; and an estimation unit 4 configured to estimate a location of the captured living-body internal image inside the living body using the similarity degrees.

公开(公告)号：US20240225536A9

公开(公告)日：2024-07-11

申请号：US17971065

申请日：2022-10-21

申请人： Case Western Reserve University ,  The Cleveland Clinic Foundation

发明人： Satish E. Viswanath ,  Florian Rieder ,  Prathyush Chirra ,  Joseph Sleiman ,  Namita Sharma Gandhi ,  Ilyssa Gordon

IPC分类号： A61B5/00 ,  G06T7/00 ,  G06T7/40 ,  G06V10/44

CPC分类号： A61B5/4842 ,  A61B5/4255 ,  A61B5/7264 ,  G06T7/0012 ,  G06T7/40 ,  G06V10/44 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/30028

摘要： The present disclosure, in some embodiments, relates to a non-transitory computer-readable medium storing computer-executable instructions that, when executed, cause a processor to perform operations, including accessing an imaging data set having one or more radiological images of a patient having Crohn's disease, the one or more radiological images including one or more intestinal strictures; identifying a plurality of determinative features from within the one or more intestinal strictures in the one or more radiological images, the plurality of determinative features being associated with one or more pathological features used to identify inflammation or fibrosis within an intestinal stricture; and applying a machine learning model to the plurality of determinative features to identify an extent of inflammation or fibrosis within the one or more intestinal strictures.

公开(公告)号：US12014488B2

公开(公告)日：2024-06-18

申请号：US17140586

申请日：2021-01-04

申请人： Case Western Reserve University ,  The United States Government as Represented by the Department of Veteran Affairs ,  UH Cleveland Medical Center

发明人： Anant Madabhushi ,  Neeraj Kumar ,  Joseph E. Willis

IPC分类号： G06T7/00 ,  G06T7/11 ,  G06T7/41 ,  G06T7/62 ,  G16H10/40 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60

CPC分类号： G06T7/0012 ,  G06T7/11 ,  G06T7/41 ,  G06T7/62 ,  G16H10/40 ,  G16H30/40 ,  G16H50/20 ,  G16H70/60 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30024 ,  G06T2207/30028 ,  G06T2207/30081 ,  G06T2207/30096

摘要： Embodiments discussed herein facilitate determination of cancer stages based at least in part on shape, size, and/or texture features of cancer nuclei. One example embodiment is a method, comprising: accessing at least a portion of a digital whole slide image (WSI) comprising a tumor; segmenting (e.g., via a first deep learning model) the tumor on the at least the portion of the digital WSI; segmenting (e.g., via a second deep learning model) cancer nuclei in the segmented tumor; extracting one or more features from the segmented cancer nuclei; providing the one or more features extracted from the segmented cancer nuclei to a trained machine learning model; and receiving, from the machine learning model, an indication of a cancer stage of the tumor.

公开(公告)号：US11934491B1

公开(公告)日：2024-03-19

申请号：US17244988

申请日：2021-04-30

申请人： Given Imaging LTD

发明人： Alexandra Gilinsky ,  Avishai Adler ,  Eshel Hason

IPC分类号： G06F18/2415 ,  A61B1/00 ,  G06N20/00 ,  G06T7/00

CPC分类号： G06F18/2415 ,  A61B1/000096 ,  G06N20/00 ,  G06T7/0012 ,  G06T2207/10068 ,  G06T2207/30028 ,  G06T2207/30092

摘要： A method for image classification includes accessing a plurality of images of at least a portion of a gastrointestinal tract (GIT) captured by a capsule endoscopy device and for each image of the plurality of images: providing a classification score for each segment of a plurality of consecutive segments of the GIT by a deep learning neural network, and providing a classification probability for each segment of the plurality of consecutive segments of the GIT based on the classification scores by a classical machine learning classifier. The method further includes determining a classification for each image to one segment of the plurality of consecutive segments of the GIT based on processing a signal corresponding to the classification probabilities of the plurality of images.

公开(公告)号：US20240081779A1

公开(公告)日：2024-03-14

申请号：US18446832

申请日：2023-08-09

申请人： FUJIFILM Corporation

发明人： Yukiya MIYACHI ,  Tetsurou EBATA

IPC分类号： A61B8/00 ,  A61B8/08 ,  A61B8/14 ,  G06T7/00 ,  G06T7/12

CPC分类号： A61B8/461 ,  A61B8/085 ,  A61B8/14 ,  A61B8/469 ,  A61B8/54 ,  G06T7/0012 ,  G06T7/12 ,  G06T2207/10132 ,  G06T2207/20104 ,  G06T2207/30028 ,  G06T2207/30061

摘要： Provided are a control method for an ultrasound diagnostic apparatus and an ultrasound diagnostic apparatus that enable a user to easily and accurately perform a diagnosis.
An ultrasound diagnostic apparatus includes: a monitor; a detection target detection unit configured to detect a detection target captured in an ultrasound image; a region-of-interest setting unit configured to set, on the ultrasound image, a region of interest including the detection target detected by the detection target detection unit; and a region-of-interest suggestion line display unit configured to display, on the monitor, a region-of-interest suggestion line consisting of only a part of a contour line of the region of interest set by the region-of-interest setting unit.

公开(公告)号：US20240020829A1

公开(公告)日：2024-01-18

申请号：US18037992

申请日：2021-11-19

申请人： DIGESTAID - ARTIFICIAL INTELLIGENCE DEVELOPMENT, LDA

发明人： João Pedro SOUSA FERREIRA ,  Miguel José DA QUINTA E COSTA DE MASCARENHAS SARAIVA ,  Hélder Manuel CASAL CARDOSO ,  Manuel Guilherme GONCALVES DE MACEDO ,  João Pedro LIMA AFONSO ,  Ana Patricia RIBEIRO ANDRADE ,  Renato Manue NATAL JORGE ,  Marco Paulo LAGES PARENTE

IPC分类号： G06T7/00 ,  A61B1/04

CPC分类号： G06T7/0012 ,  A61B1/041 ,  G06T2207/10068 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30096 ,  G06T2207/30028

摘要： The present invention relates to a computer-implemented method capable of automatically detecting small bowel and colonic ulcers and erosions in Crohn's capsule endoscopy image data, by classifying pixels as lesion or non-lesion, using a convolutional image feature extraction step followed by a classification step and indexing such lesions in the set of one or more classes.

公开(公告)号：US11869190B2

公开(公告)日：2024-01-09

申请号：US17713026

申请日：2022-04-04

申请人： Niigata University ,  Denka Company Limited

发明人： Toshifumi Wakai ,  Shujiro Okuda ,  Yoshifumi Shimada ,  Hiroshi Izutsu ,  Keisuke Kodama

IPC分类号： G06K9/00 ,  G06T7/00 ,  G01N1/30 ,  G01N33/483

CPC分类号： G06T7/0014 ,  G01N1/30 ,  G01N33/4833 ,  G01N2001/302 ,  G06T2207/10024 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/30028 ,  G06T2207/30096

摘要： A method, a program, and a method determining hypermutated type cancer with higher accuracy than before is provided.
Provided is a system for determining hypermutated cancer comprising, an input unit configured to be capable of inputting a plurality of first image data, a plurality of second image data and a plurality of third image data, wherein the first image data represents an image of a pathological section of stained hypermutated cancer, the second image data represents an image of a pathological section of cancer which is not hypermutated, and is stained same as the pathological section of the first image data, and the third image data represents an image of a pathological section of cancer which is newly determined whether hypermutated or not, and is stained same as the pathological section of the first image data, a holding unit configured to be capable of holding a first image data and a second image data, a machine learning execution unit configured to be capable of generating a determination model determining whether a cancer is hypermutated or not, using the first image data and the second image data held by the holding unit as training data, and a determining unit configured to be capable of determining whether the third image data represents an image of hypermutated cancer or not, by inputting the third image data into the determination model.

公开(公告)号：US20230410295A1

公开(公告)日：2023-12-21

申请号：US18037980

申请日：2021-11-18

申请人： DIGESTAID - ARTIFICIAL INTELLIGENCE DEVELOPMENT, LDA

发明人： João Pedro SOUSA FERREIRA ,  Miguel José DA QUINTA E COSTA DE MASCARENHAS SARAIVA ,  Hélder Manuel CASAL CARDOSO ,  Manuel Guilherme GONCALVES DE MACEDO ,  João Pedro LIMA AFONSO ,  Ana Patricia RIBEIRO ANDRADE ,  Renato Manue NATAL JORGE ,  Marco Paulo LAGES PARENTE

IPC分类号： G06T7/00 ,  G06V10/764 ,  G06V10/776 ,  G06V10/94 ,  G06V10/77 ,  G06N3/045 ,  G06N3/096

CPC分类号： G06T7/0012 ,  G06V10/764 ,  G06V10/776 ,  G06V10/945 ,  G06V10/7715 ,  G06N3/045 ,  G06N3/096 ,  G06T2207/30028 ,  G06T2207/30096 ,  G06T2207/20084 ,  G06T2207/20081 ,  G06T2207/20092 ,  G06T2207/10068 ,  G06V2201/03 ,  A61B1/041

摘要： The present invention relates to a computer-implemented method, capable of automatically detecting clinically relevant colonic pleomorphic lesions and blood or hematic traces in colon capsule endoscopy images, by classifying pixels as colonic pleomorphic lesions or blood or hematic traces, using a convolutional image feature extraction step followed by a classification and indexing step of such findings into a set of one or more classes.

公开(公告)号：US11800969B2

公开(公告)日：2023-10-31

申请号：US16986232

申请日：2020-08-05

申请人： Wuhan Endoangel Medical Technology Co., Ltd.

发明人： Honggang Yu ,  Bin Liu ,  Shan Hu ,  Lianlian Wu

IPC分类号： A61B1/00 ,  G06T7/10 ,  G06T3/40 ,  G06T7/00 ,  G06T7/20 ,  G06T11/60

CPC分类号： A61B1/00009 ,  G06T3/4007 ,  G06T7/0014 ,  G06T7/10 ,  G06T7/20 ,  G06T11/60 ,  G06T2207/10016 ,  G06T2207/10068 ,  G06T2207/20132 ,  G06T2207/30028

摘要： A method for monitoring a colonoscope withdrawal speed, the method including: 1) acquiring, a real-time video of colonoscopy, decoding the video into images, cropping the images, and zooming-out the images cropped where texture information of the images is retained; 2) converting the images including the texture information to grayscale images; 3) obtaining Hash fingerprints of the images; 4) calculating a Hamming distance between the images; 5) comparing the Hash fingerprints of a current colonoscopy image with n previous colonoscopy images, to obtain an overlapping rate of the current colonoscopy image with any one of the n previous colonoscopy images; 6) calculating a weighted similarity of the images at a point in time t; 7) converting a weighted overlapping rate of the images at the point in time t into a stability coefficient; and 8) calculating a mean stability coefficient of colonoscopy images within a period of time 0-t.

公开(公告)号：US20230326072A1

公开(公告)日：2023-10-12

申请号：US18022150

申请日：2021-08-16

申请人： ANKON TECHNOLOGIES CO., LTD

发明人： Tianyi YANGDAI ,  Wenjin YUAN ,  Yi LI ,  Hao LIU

IPC分类号： G06T7/73 ,  A61B1/04 ,  A61B1/045

CPC分类号： G06T7/74 ,  A61B1/041 ,  A61B1/045 ,  G06T2207/10068 ,  G06T2207/30028

摘要： The present invention provides an image-based position detection method, an electronic device, and a readable storage medium. The method includes: driving a capsule endoscope to continuously capture a group of images at an interval of a first preset time t1, where each group of images comprises at least one image; obtaining at least one image from each group of images, and calculating a determination index according to grayscale values of at least two channels of the image; determining whether the capsule endoscope reaches a preset detection position according to a value of the determination index; if yes, adjusting the capsule endoscope to a corresponding working mode according to a current position of the capsule endoscope, and if no, continue monitoring. The present invention can determine whether the capsule endoscope reaches the preset detection position, which greatly save battery power, and improve work efficiency of the capsule endoscope.