公开(公告)号：US11972571B2

公开(公告)日：2024-04-30

申请号：US17497954

申请日：2021-10-10

Applicant: Infervision Medical Technology Co., Ltd.

Inventor： Enyou Liu ,  Shaokang Wang ,  Kuan Chen

IPC: G06T7/11 ,  G06F18/21 ,  G06F18/213 ,  G06F18/25 ,  G06N3/045 ,  G06T5/70 ,  G06T7/187 ,  G06T7/194

CPC classification number: G06T7/11 ,  G06F18/213 ,  G06F18/217 ,  G06F18/253 ,  G06N3/045 ,  G06T5/70 ,  G06T7/187 ,  G06T7/194 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20212 ,  G06T2207/30101 ,  G06V2201/03

Abstract: The method for image segmentation includes: acquiring, according to an image to be segmented including a background, a mediastinum, an artery and a vein, a first segmentation result of the mediastinum, the artery, the vein and the background in a mediastinum region of the image to be segmented; acquiring, according to the image to be segmented, a second segmentation result of a blood vessel and the background in an epitaxial region of the image to be segmented; and acquiring, according to the first segmentation result and the second segmentation result, a segmentation result of the mediastinum, the artery, the vein and the background of the image to be segmented, so that the segmentation accuracy and the segmentation efficiency of the artery and the vein may be improved.

公开(公告)号：US10937157B2

公开(公告)日：2021-03-02

申请号：US16351896

申请日：2019-03-13

Applicant: Infervision Medical Technology Co., Ltd.

Inventor： Rongguo Zhang ,  Mengmeng Sun ,  Shaokang Wang ,  Kuan Chen

IPC: G06T7/00 ,  G06N20/00 ,  G06N3/08 ,  G06T7/11

Abstract: A computed tomography (CT) pulmonary nodule detection method based on deep learning is provided. The method comprises the steps of: acquiring 3D pulmonary CT sequence images of a user; processing the acquired 3D pulmonary CT sequence images into 2D image data; inputting 2D image data into a preset deep learning network model for training to obtain a trained pulmonary nodule detection model; inputting a set of 3D pulmonary CT sequence images to be tested into the trained pulmonary nodule detection model to obtain a preliminary pulmonary nodule detection result; applying a pulmonary region segmentation algorithm based on deep learning to the preliminary pulmonary nodule detection result to remove false positive pulmonary nodules, so as to obtain a final pulmonary nodule detection result.

公开(公告)号：US12249075B2

公开(公告)日：2025-03-11

申请号：US17676133

申请日：2022-02-19

Applicant: Infervision Medical Technology Co., Ltd.

Inventor： Yanfeng Sun ,  Shaokang Wang ,  Kuan Chen

IPC: G06T7/11 ,  G06V10/764 ,  G06V20/70

Abstract: Disclosed are a method and an apparatus of processing image. The method includes: obtaining an initial bone segmentation result; and fusing the initial bone segmentation result based on characteristics of and correspondences between a plurality of bone segmentation results in the initial bone segmentation result, to obtain a target bone segmentation result. The initial bone segmentation result includes the plurality of bone segmentation results generated by a plurality of different deep learning models. Methods in the embodiments of the present application can improve precision of a fusion result of the plurality of bone segmentation results.

公开(公告)号：US11954860B2

公开(公告)日：2024-04-09

申请号：US17398790

申请日：2021-08-10

Applicant: Infervision Medical Technology Co., Ltd.

Inventor： Mengmeng Sun ,  Shaokang Wang ,  Kuan Chen

IPC: G06T7/00 ,  A61B6/03 ,  G06T7/33 ,  G06T7/38

CPC classification number: G06T7/0016 ,  G06T7/33 ,  G06T7/38 ,  A61B6/032 ,  G06T2207/10016 ,  G06T2207/10081 ,  G06T2207/30096

Abstract: Disclosed are an image matching method, an image matching device, and a storage medium. A first image sequence and a second image sequence are acquired, and thus a first object and a second object are reconstructed and generated based on the first image sequence and the second image sequence respectively. The registration of the first object and the second object are further performed, and a mapping relationship obtained according to a registration result may indicate a correspondence between image frames in the first image sequence and image frames in the second image sequence. Compared with setting a difference value artificially, obtaining the correspondence between image frames in the first image sequence and image frames in the second image sequence by using the image matching method improves the matching accuracy.