公开(公告)号：US11893811B2

公开(公告)日：2024-02-06

申请号：US17326541

申请日：2021-05-21

Applicant: Carnegie Mellon University ,  UNIVERSITY OF PITTSBURGH—OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION

Inventor： Daniel Clymer ,  Jonathan Cagan ,  Philip LeDuc ,  Liron Pantanowitz ,  Janet Catov

IPC: G06V20/69 ,  G06T7/00 ,  G06F18/10 ,  G06F18/241 ,  G06F18/2135 ,  G06F18/214 ,  G06F18/2415 ,  G06V40/14

CPC classification number: G06V20/69 ,  G06F18/10 ,  G06F18/2135 ,  G06F18/2148 ,  G06F18/241 ,  G06F18/2415 ,  G06T7/0012 ,  G06V20/695 ,  G06V20/698 ,  G06T2207/10056 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/30101 ,  G06V40/14 ,  G06V2201/031

Abstract: A hierarchical deep-learning object detection framework provides a method for identifying objects of interest in high-resolution, high pixel count images, wherein the objects of interest comprise a relatively a small pixel count when compared to the overall image. The method uses first deep-learning model to analyze the high pixel count images, in whole or as a patchwork, at a lower resolution to identify objects, and a second deep-learning model to analyze the objects at a higher resolution to classify the objects.

公开(公告)号：US20230419693A1

公开(公告)日：2023-12-28

申请号：US18463271

申请日：2023-09-07

Applicant: FUJIFILM Corporation

Inventor： Misaki GOTO

IPC: G06V20/60 ,  G06V20/50 ,  G06V10/77 ,  G16H30/40 ,  A61B8/12 ,  A61B8/08

CPC classification number: G06V20/60 ,  G06V20/50 ,  G06V10/77 ,  G16H30/40 ,  A61B8/12 ,  A61B8/5207 ,  A61B8/085 ,  G06V2201/031

Abstract: A medical image processing apparatus according to an aspect of the present invention is a medical image processing apparatus including a processor. The processor is configured to execute an image acquisition process for sequentially acquiring time-series medical images; a drawing information acquisition process for acquiring drawing information drawn in the medical images; a drawing information recognition process for recognizing the acquired drawing information; a target object recognition process for recognizing a target object from the medical images; a notification level determination process for determining a notification level for the target object by using the recognized drawing information; and a display process for causing a display device to display the target object at the determined notification level.

公开(公告)号：US20230386139A1

公开(公告)日：2023-11-30

申请号：US18029029

申请日：2020-09-28

Applicant: KOMPATH, INC. ,  The University of Tokyo

Inventor： Takehito Doke ,  Haruaki Takahashi ,  Toki Saito ,  Taichi Kin ,  Hiroshi Oyama ,  Nobuhito Saito

IPC: G06T19/00 ,  G06T7/73 ,  G06V20/70 ,  A61B90/00

CPC classification number: G06T19/00 ,  G06T7/73 ,  G06V20/70 ,  A61B90/37 ,  G06T2219/004 ,  G06T2200/04 ,  G06T2207/30004 ,  G06T2207/20104 ,  G06V2201/031 ,  G06T2210/41

Abstract: A medical image processing device acquires a user operation. The medical image processing device specifies, from a three-dimensional medical image in which one or more organs appear, an organ of interest to which to apply information. The medical image processing device applies predetermined information to the organ of interest that has been specified. The medical image processing device controls a display device so as to display the three-dimensional medical image.

公开(公告)号：US11813047B2

公开(公告)日：2023-11-14

申请号：US17335518

申请日：2021-06-01

Applicant: University of Virginia Patent Foundation

Inventor： Craig H. Meyer ,  Anudeep Konda ,  Christopher M. Kramer ,  Xue Feng

IPC: G06T7/00 ,  G06T7/62 ,  G06T7/13 ,  G06T7/70 ,  G06K9/62 ,  A61B5/029 ,  A61B5/026 ,  A61B5/00 ,  A61B5/107 ,  G06T7/11 ,  G06F18/211 ,  G06V10/764 ,  G06V10/82

CPC classification number: A61B5/0263 ,  A61B5/029 ,  A61B5/1071 ,  A61B5/1075 ,  A61B5/7267 ,  G06F18/211 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/13 ,  G06T7/62 ,  G06T7/70 ,  G06V10/764 ,  G06V10/82 ,  G06T2207/10088 ,  G06T2207/20084 ,  G06T2207/30048 ,  G06V2201/031

Abstract: In one aspect the disclosed technology relates to embodiments of a method which, includes acquiring magnetic resonance imaging data, for a plurality of images, of the heart of a subject. The method also includes segmenting, using cascaded convolutional neural networks (CNN), respective portions of the images corresponding to respective epicardium layers and endocardium layers for a left ventricle (LV) and a right ventricle (RV) of the heart. The segmenting is used for extracting biomarker data from segmented portions of the images and, in one embodiment, assessing hypertrophic cardiomyopathy from the biomarker data. The method further includes segmenting processes for T1 MRI data and LGE MRI data.

公开(公告)号：US20230316520A1

公开(公告)日：2023-10-05

申请号：US17657676

申请日：2022-04-01

Applicant: GE Precision Healthcare LLC

Inventor： Hani Mirar

IPC: G06T7/00 ,  G06T7/246 ,  G06T7/11 ,  G06V10/22 ,  G06V10/26

CPC classification number: G06T7/0014 ,  G06T7/248 ,  G06T7/11 ,  G06V10/235 ,  G06V10/26 ,  G06T2207/20104 ,  G06T2207/30048 ,  G06T2207/10132 ,  G06V2201/031

Abstract: Various methods and systems are provided for a medical imaging system. In one embodiment, a method comprises generating cardiac ultrasound images from ultrasound imaging data of a heart, excluding pericardium depicted in the cardiac ultrasound images, and calculating strain values of a myocardium region of interest in the cardiac ultrasound images while excluding the pericardium depicted in the cardiac ultrasound images. In this way, the strain values may be calculated more accurately by not including information from the non-contractile pericardium.

公开(公告)号：US11776216B2

公开(公告)日：2023-10-03

申请号：US17305248

申请日：2021-07-02

Applicant: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.

Inventor： Weipin Nie ,  Yue Gao ,  Hao Zeng ,  Chao Fu ,  Ce Wang

IPC: G06T19/00 ,  G06T7/11 ,  G06T7/187 ,  G06T19/20 ,  G06T7/12 ,  G06V10/25

CPC classification number: G06T19/00 ,  G06T7/11 ,  G06T7/12 ,  G06T7/187 ,  G06T19/20 ,  G06V10/25 ,  G06T2207/20104 ,  G06T2207/30056 ,  G06T2207/30096 ,  G06T2207/30101 ,  G06T2210/41 ,  G06T2219/028 ,  G06T2219/2021 ,  G06V2201/031

Abstract: The present disclosure relates to a system and method for extracting a region of interest. Image data in a first sectional plane may be acquired. The image data in the first sectional plane may include at least one first slice image and one second slice image. A first region of interest (ROI) in the first slice image may be determined. A second ROI in the second slice image may be determined. A first volume of interest (VOI) may be determined based on the first ROI, the second ROI, and characteristic information of the image data in the first sectional plane.

公开(公告)号：US11749401B2

公开(公告)日：2023-09-05

申请号：US17084875

申请日：2020-10-30

Applicant: Guerbet

Inventor： Yi-Qing Wang ,  Giovanni John Jacques Palma

IPC: G16H30/40 ,  G06T7/00 ,  G06T7/187 ,  G06T5/00 ,  G06T19/20 ,  G06F18/2413

CPC classification number: G16H30/40 ,  G06F18/24147 ,  G06T5/002 ,  G06T7/0012 ,  G06T7/187 ,  G06T19/20 ,  G06T2207/20081 ,  G06T2207/30096 ,  G06T2219/004 ,  G06V2201/031

Abstract: A mechanism is provided for seed relabeling for seed-based slice-wise lesion segmentation. The mechanism receives a lesion mask for a three-dimensional medical image volume. The lesion mask corresponds to detected lesions in the medical image volume and wherein each detected lesion has a lesion contour. The mechanism generates a distance map for a given two-dimensional slice in the medical image volume based on the lesion mask. The distance map comprises a distance to a lesion contour for each voxel of the given two-dimensional slice. The mechanism performs local maxima identification to select a set of local maxima from the distance map such that each local maximum has a value greater than its immediate neighbor points. The mechanism performs seed relabeling based on the distance map and the set of local maxima to generate a set of seeds. Each seed represents a center of a distinct component of a lesion contour. The mechanism performs image segmentation on the lesion mask based on the set of seeds to form a split lesion mask.

公开(公告)号：US11717233B2

公开(公告)日：2023-08-08

申请号：US16947149

申请日：2020-07-21

Applicant: Siemens Healthcare GmbH

Inventor： Florin-Cristian Ghesu ,  Siqi Liu ,  Awais Mansoor ,  Sasa Grbic ,  Sebastian Vogt ,  Dorin Comaniciu ,  Ruhan Sa ,  Zhoubing Xu

IPC: A61B5/00 ,  G06T7/62 ,  G06T7/11 ,  G16H50/20 ,  G16H30/40 ,  A61B6/03 ,  A61B6/00 ,  G06T7/00 ,  G06F18/214

CPC classification number: A61B5/7275 ,  A61B5/7267 ,  A61B6/032 ,  A61B6/50 ,  G06F18/214 ,  G06T7/0012 ,  G06T7/11 ,  G06T7/62 ,  G16H30/40 ,  G16H50/20 ,  G06T2207/10081 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20221 ,  G06T2207/30061 ,  G06V2201/031

Abstract: Systems and methods for assessing a disease are provided. An input medical image in a first modality is received. Lungs are segmented from the input medical image using a trained lung segmentation network and abnormality patterns associated with the disease are segmented from the input medical image using a trained abnormality pattern segmentation network. The trained lung segmentation network and the trained abnormality pattern segmentation network are trained based on 1) synthesized images in the first modality generated from training images in a second modality and 2) target segmentation masks for the synthesized images generated from training segmentation masks for the training images. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality patterns.

公开(公告)号：US20230237665A1

公开(公告)日：2023-07-27

申请号：US18191856

申请日：2023-03-28

Applicant: SHANGHAI UNITED IMAGING HEALTHCARE CO., LTD.

Inventor： Chaoran LIU ,  Yang LI

IPC: G06T7/11 ,  G06T7/33 ,  G06T7/00 ,  G06V10/26

CPC classification number: G06T7/11 ,  G06T7/33 ,  G06T7/0012 ,  G06V10/26 ,  G06V2201/031 ,  G06T2207/10088 ,  G06T2207/10081

Abstract: Systems and methods for image segmentation are provided. The systems may obtain a target image and a template image relating to the target image. The template image may correspond to an initial mask reflecting initial segmentations of the template image. The systems may determine a first transformation and an intermediate template image by preliminarily registering the template image to the target image and generate an intermediate mask based on the initial mask and the first transformation. The systems may determine, based on the intermediate mask, one or more first regions from the target image and one or more second regions from the intermediate template image. The systems may determine a second transformation by registering each of the one or more second regions to a corresponding first region. The systems may determine a target mask according to which the target image can be segmented based on one or more second transformations.

公开(公告)号：US20230237661A1

公开(公告)日：2023-07-27

申请号：US18100525

申请日：2023-01-23

Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA

Inventor： Albert HSIAO ,  Kyle HASENSTAB

IPC: G06T7/00 ,  G06T7/30 ,  G06V10/82 ,  G06V10/75

CPC classification number: G06T7/0016 ,  G06T7/30 ,  G06V10/82 ,  G06V10/754 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30061 ,  G06V2201/031

Abstract: A method and system for automated deformable registration of an organ from medical images includes generating segmentations of the organ by processing a first and second series of images corresponding to different organ states using a first trained CNN. A second trained CNN processes the first and second series of images and the segmentations to deformably register the second series of images to the first series of images. The second trained CNN predicts a displacement field by minimizing a registration loss function, where the displacement field maximizes colocalization of the organ between the different states.