公开(公告)号：US20240312009A1

公开(公告)日：2024-09-19

申请号：US18576722

申请日：2023-07-06

Applicant: Versitech Limited ,  The Education University of Hong Kong

Inventor： Keith Wan Hang CHIU ,  Wai Kay Walter SETO ,  Gilbert Chiu Sing LUI ,  Jianliang LU ,  Man Fung YUEN ,  Philip Leung Ho YU

IPC: G06T7/00 ,  G06T3/40 ,  G06V10/44 ,  G06V10/764 ,  G06V10/80 ,  G16H50/20

CPC classification number: G06T7/0012 ,  G06T3/40 ,  G06V10/44 ,  G06V10/764 ,  G06V10/806 ,  G16H50/20 ,  G06T2207/10081 ,  G06T2207/10088 ,  G06T2207/30096 ,  G06V2201/03

Abstract: A three dimensional classification system for recognizing cross-sectional images automatically contains a processor that executes: (1) rescaling of a plurality of cross-sectional images; and feeding the rescaled plurality of cross-sectional images into two branches; (2) feeding the rescaled plurality of cross-sectional images into a first branch for performing a plurality of convolutions on the rescaled plurality of cross-sectional images directly to learn features for distinguishing phases; (3) feeding the rescaled plurality of cross-sectional images into a second branch for reducing resolution, and then performing a plurality of convolutions on the reduced resolution plurality of cross-sectional images to learn features for distinguishing phases; and (4) concatenating convolutional output channels from the two branches to fuse global and local features, on which two fully-connected layers are stacked as a classifier to recognize cross-sectional volumetric images accurately and quickly.

公开(公告)号：US20240303815A1

公开(公告)日：2024-09-12

申请号：US18667146

申请日：2024-05-17

Applicant: THE ASAN FOUNDATION ,  UNIVERSITY OF ULSAN FOUNDATION FOR INDUSTRY COOPERATION

Inventor： Jungsu OH ,  Jae Seung KIM ,  Minyoung OH ,  Dong Yun LEE ,  Seung Jun OH ,  Sang Ju LEE

IPC: G06T7/00 ,  A61B6/03 ,  A61B6/50 ,  A61K51/04 ,  G06V10/774

CPC classification number: G06T7/0012 ,  A61B6/037 ,  A61B6/507 ,  A61K51/0491 ,  G06V10/774 ,  G06T2207/10016 ,  G06T2207/10104 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30104 ,  G06V2201/03

Abstract: The present invention relates to a method for predicting a state of an object on the basis of dynamic image data and a computing device performing same, the method enabling initial dynamic image data and delay image data to be predicted by performing learning on the basis of dynamic image data captured at a time point when both blood flow image information and disease-specific biological information are included, and furthermore, enabling blood flow image information and disease-specific biological information of the object to be provided.

公开(公告)号：US20240299105A1

公开(公告)日：2024-09-12

申请号：US18439056

申请日：2024-02-12

Applicant: IX Innovation LLC

Inventor： Jeffrey Roh ,  Justin Esterberg ,  John Cronin ,  Seth Cronin ,  Michael John Baker

IPC: A61B34/00 ,  G06T7/00 ,  G06V10/40 ,  G10L13/02 ,  G10L15/06 ,  G10L15/22 ,  G10L15/26 ,  G10L15/30 ,  G16B20/20 ,  G16B40/20 ,  G16H10/60 ,  G16H50/20 ,  G16H50/50

CPC classification number: A61B34/25 ,  G06T7/0012 ,  G06V10/40 ,  G10L13/02 ,  G10L15/063 ,  G10L15/22 ,  G10L15/26 ,  G10L15/30 ,  G16B20/20 ,  G16B40/20 ,  G16H10/60 ,  G16H50/20 ,  G16H50/50 ,  A61B2034/256 ,  G06T2207/30004 ,  G06V2201/03

Abstract: Methods, apparatuses, and systems for transcribing and performing analysis on patient data are disclosed. Data is collected from one or more medical professionals as well as sensors and imaging devices positioned on or oriented towards a patient. An analysis is performed on the patient data and the data is presented to a medical professional via a verbal interface in a conversational manner, allowing the medical professional to provide additional data such as observations or instructions which may be used for further analysis or to perform actions related to the patient's care.

公开(公告)号：US20240296935A1

公开(公告)日：2024-09-05

申请号：US18438640

申请日：2024-02-12

Applicant: Siemens Healthineers AG

Inventor： Yue Zhang ,  Marc Demoustier ,  Venkatesh Narasimha Murthy ,  Florin-Cristian Ghesu ,  Dorin Comaniciu

IPC: G16H30/40 ,  G06T7/12 ,  G06T7/20 ,  G06T9/00 ,  G06V10/80

CPC classification number: G16H30/40 ,  G06T7/12 ,  G06T7/20 ,  G06T9/00 ,  G06V10/806 ,  G06V2201/03 ,  G06V2201/07

Abstract: A position prediction of a target is provided based on a segmentation of a context of the target. Alternatively, or additionally, to a spatial context of the target, it is also possible to consider a temporal context. A catheter tip can be tracked.

公开(公告)号：US20240282434A1

公开(公告)日：2024-08-22

申请号：US18650347

申请日：2024-04-30

Applicant: Lunit Inc. ,  SEOUL NATIONAL UNIVERSITY HOSPITAL

Inventor： Min Chul KIM ,  Chang Min PARK ,  Eui Jin HWANG

IPC: G16H30/40 ,  A61B6/00 ,  A61B6/46 ,  A61B34/10 ,  A61M1/04 ,  G06F18/2431 ,  G06N20/00 ,  G06T7/00 ,  G06T7/11 ,  G06T7/70 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G16H50/20

CPC classification number: G16H30/40 ,  A61B6/5217 ,  A61B34/10 ,  A61M1/04 ,  G06F18/2431 ,  G06N20/00 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/70 ,  G06V10/25 ,  G06V10/764 ,  G06V10/82 ,  G16H50/20 ,  A61B6/461 ,  A61B2034/107 ,  G06T2207/20081 ,  G06T2207/30012 ,  G06T2207/30061 ,  G06V2201/03

Abstract: Some embodiments of the present disclosure provide a pneumothorax detection method performed by a computing device. The method may comprise obtaining predicted pneumothorax information, predicted tube information, and a predicted spinal baseline with respect to an input image from a trained pneumothorax prediction model; determining at least one pneumothorax representative position for the predicted pneumothorax information and at least one tube representative position for the predicted tube information, in a prediction image in which the predicted pneumothorax information and the predicted tube information are displayed; dividing the prediction image into a first region and a second region by the predicted spinal baseline; and determining a region in which the at least one pneumothorax representative position and the at least one tube representative position exist among the first region and the second region.

公开(公告)号：US20240282084A1

公开(公告)日：2024-08-22

申请号：US18581231

申请日：2024-02-19

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Francesco Dalla SERRA ,  Alison O'NEIL ,  Chaoyang WANG

IPC: G06V10/774 ,  G06T7/00 ,  G06V10/22 ,  G06V10/80 ,  G06V10/82 ,  G06V20/70

CPC classification number: G06V10/774 ,  G06T7/0016 ,  G06V10/235 ,  G06V10/806 ,  G06V10/82 ,  G06V20/70 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06V2201/03

Abstract: A data processing apparatus configured to train an image analysis model to perform a task relating to input data which includes at least image data, wherein the data processing apparatus comprises processing circuitry configured to:



receive the input data;
generate image tokens for inputting to the image analysis model by applying a visual extractor model that is trained to identify an anatomical region included in the image data which is comprised in the input data and to determine a label relating to a pre-determined sub-task relating to said anatomical region; and
train the image analysis model by inputting at least the image tokens.

公开(公告)号：US12064215B2

公开(公告)日：2024-08-20

申请号：US18110135

申请日：2023-02-15

Applicant: Vektor Medical, Inc.

Inventor： Christopher Villongco

IPC: A61B5/271 ,  A61B5/00 ,  A61B5/02 ,  A61B5/318 ,  A61B5/319 ,  A61B5/339 ,  A61B5/341 ,  A61B34/10 ,  G06V10/00 ,  G06V10/764 ,  G09B23/30 ,  A61B5/107 ,  A61B5/25 ,  A61B5/316 ,  A61B5/349 ,  A61B5/361 ,  A61B5/363 ,  A61B5/364 ,  A61B6/03 ,  A61B6/50 ,  G06F18/22 ,  G06F30/20 ,  G06N3/045 ,  G06N3/08 ,  G06N5/04 ,  G06N5/046 ,  G06N20/00 ,  G06T3/4007 ,  G06T17/20 ,  G06T19/20 ,  G09B23/28 ,  G16H50/20 ,  G16H50/50

CPC classification number: A61B5/02028 ,  A61B5/318 ,  A61B5/319 ,  A61B5/339 ,  A61B5/341 ,  A61B5/7275 ,  A61B5/743 ,  A61B5/7435 ,  A61B34/10 ,  G06V10/00 ,  G06V10/764 ,  G09B23/30 ,  A61B5/1075 ,  A61B5/25 ,  A61B5/316 ,  A61B5/349 ,  A61B5/361 ,  A61B5/363 ,  A61B5/364 ,  A61B5/6805 ,  A61B5/7235 ,  A61B5/725 ,  A61B5/7267 ,  A61B5/7425 ,  A61B5/7445 ,  A61B6/032 ,  A61B6/503 ,  A61B2034/105 ,  G06F18/22 ,  G06F30/20 ,  G06N3/045 ,  G06N3/08 ,  G06N5/04 ,  G06N5/046 ,  G06N20/00 ,  G06T3/4007 ,  G06T17/205 ,  G06T19/20 ,  G06T2210/41 ,  G06V2201/03 ,  G09B23/285 ,  G16H50/20 ,  G16H50/50

Abstract: Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.

公开(公告)号：US20240273720A1

公开(公告)日：2024-08-15

申请号：US18641184

申请日：2024-04-19

Applicant: Tencent Technology (Shenzhen) Company Limited

Inventor： Zhongyi Yang ,  Sen Yang ,  Jinxi Xiang ,  Jun Zhang ,  Xiao Han

IPC: G06T7/00 ,  G06T3/40 ,  G06T7/11 ,  G06T7/194 ,  G06V10/42 ,  G06V10/44 ,  G06V10/764

CPC classification number: G06T7/0012 ,  G06T3/40 ,  G06T7/11 ,  G06T7/194 ,  G06V10/42 ,  G06V10/44 ,  G06V10/764 ,  G06T2207/20076 ,  G06T2207/20081 ,  G06T2207/30096 ,  G06V2201/03

Abstract: This application discloses a method for determining a lesion region, and a model training method and apparatus, and relates to the field of computer vision technologies. The method includes the following steps: sampling a pathological image by a first sampling way to obtain at least two first instance images (310); determining a candidate lesion region in the pathological image, based on feature information extracted from the at least two first instance images (320); sampling the candidate lesion region by a second sampling way to obtain at least two second instance images, where an overlap degree between the second instance images is greater than that between the first instance images (330); and determining lesion indication information of the pathological image, based on feature information extracted from the at least two second instance images, where the lesion indication information is used for indicating the lesion region in the pathological image (340). In this application, the consumption of human resources is reduced, and costs required to determine the lesion region are saved.

公开(公告)号：US20240268711A1

公开(公告)日：2024-08-15

申请号：US18432599

申请日：2024-02-05

Applicant: Samsung Electronics Co., Ltd.

Inventor： Migyeong Gwak ,  Korosh Vatanparvar ,  Li Zhu ,  Michael Chan ,  Nafiul Rashid ,  Jungmok Bae ,  Jilong Kuang ,  Jun Gao

IPC: A61B5/113 ,  A61B5/00 ,  A61B5/08 ,  G06V40/16

CPC classification number: A61B5/113 ,  A61B5/08 ,  A61B5/7264 ,  A61B5/7275 ,  G06V40/171 ,  G06V2201/03

Abstract: A method includes capturing a video of a person's face using a camera. The method also includes determining a motion-based respiratory rate (RR) and a motion-based respiratory signal based on the video of the person's face. The method further includes determining a remote photoplethysmography (rPPG)-based RR and an rPPG-based respiratory signal based on the video of the person's face. The method also includes predicting whether the motion-based RR or the rPPG-based RR is more likely to be accurate using a trained machine learning model that receives the motion-based respiratory signal and the rPPG-based respiratory signal as input. In addition, the method includes presenting one of the motion-based RR or the rPPG-based RR based on the prediction.

公开(公告)号：US12062168B2

公开(公告)日：2024-08-13

申请号：US17305631

申请日：2021-07-12

Applicant: SIEMENS HEALTHINEERS AG

Inventor： Felix Meister ,  Tiziano Passerini ,  Tommaso Mansi ,  Eric Lluch Alvarez ,  Chloé Audigier ,  Viorel Mihalef

IPC: G06T7/00 ,  A61B6/00 ,  G06F18/22 ,  G06F18/231 ,  G06F18/243 ,  G06T7/11 ,  A61B6/50

CPC classification number: G06T7/0012 ,  A61B6/5217 ,  G06F18/22 ,  G06F18/231 ,  G06F18/24323 ,  G06T7/11 ,  A61B6/50 ,  G06T2207/20076 ,  G06T2207/30061 ,  G06V2201/03

Abstract: Systems and methods for estimating local conductivities from anatomical information derived from MR images, ECG, and sparse contact maps are provided. ECG features and sparse measurements are mapped to an anatomical model represented as a graph. Graph convolutional layers and a multilayer perceptron are applied to extract local and global features respectively. The local and global features are combined and further processed by a series of fully connected layers to regress a set of vertex conductivities.