公开(公告)号：US20240087118A1

公开(公告)日：2024-03-14

申请号：US18459816

申请日：2023-09-01

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Gengwan LI ,  Lixin YAN ,  Qilin XIAO ,  Shun ZHAO

IPC: G06T7/00 ,  G06V10/25 ,  G06V10/44

CPC classification number: G06T7/0012 ,  G06V10/25 ,  G06V10/44 ,  G06T2207/20081 ,  G06V2201/07

Abstract: A medical image processing apparatus according to one embodiment includes processing circuitry. The processing circuitry trains an attention model by using a medical image and a mask image that is obtained by performing mask processing on a region other than a region of interest in the medical image, trains an image processing model by using the medical image, a heatmap corresponding to the medical image, and an attention feature that indicates attention of the region of interest in the trained attention model, combines, as an attention image processing model, an attention extraction module that includes an attention module for outputting the attention feature and the trained image processing model, performs processing on the medical image by using the attention image processing model, and generates a heatmap for determining a position of a landmark in the medical image.

公开(公告)号：US20240303821A1

公开(公告)日：2024-09-12

申请号：US18599801

申请日：2024-03-08

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Xiao XUE ,  Gengwan LI ,  Bing HAN

IPC: G06T7/11 ,  G06T7/00 ,  G16H30/20 ,  G16H30/40

CPC classification number: G06T7/11 ,  G06T7/0012 ,  G16H30/20 ,  G16H30/40 ,  G06T2207/20081 ,  G06T2207/30056 ,  G06T2207/30061 ,  G06T2207/30101

Abstract: A segmentation model learning method according to an embodiment includes learning that, based on a loss function value, includes performing supervised learning of the voxels in medical image data according to the region to which the voxels belong. The learning of the medical image data includes: using first-type labeling information, which is meant for segmenting a predetermined structure into a plurality of categories, about the voxels of a predetermined structure and causing a segmentation model to perform direct supervised learning that represents learning for segmentation of the predetermined structure into a plurality of categories; using second-type labeling information, which is meant for segmenting a massive region covering the predetermined structure into a plurality of blocks, about the voxels of a massive region and causing the segmentation model to perform indirect supervised learning that represents learning for segmentation of the massive region into a plurality of categories; and optimizing the network parameters of the segmentation model.

公开(公告)号：US20250069231A1

公开(公告)日：2025-02-27

申请号：US18814456

申请日：2024-08-23

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Xiao XUE ,  Gengwan LI ,  Bing HAN ,  Bing LI

IPC: G06T7/11

Abstract: An image segmentation apparatus according to an embodiment of the present disclosure includes processing circuitry. The processing circuitry is configured to obtain a massive region to which labeling information is attached and a tubular region to which labeling information is attached. By using the labeling information of the massive region and the labeling information of the tubular region, the processing circuitry is configured to generate a region to be segmented and a non-boundary region, by carrying out a distance transformation. The processing circuitry is configured to generate a classifier for classifying spatial coordinates, by using the labeling information of the non-boundary region and labeling information in a specific position determined on the basis of the region to be segmented and the tubular region. The processing circuitry is configured to segment voxels in the region to be segmented by using the classifier and to thus determine a final segmentation result.

公开(公告)号：US20230058183A1

公开(公告)日：2023-02-23

申请号：US17814904

申请日：2022-07-26

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Yanhua WANG ,  Bing LI ,  Qilin XIAO ,  Fuyue WANG ,  Gengwan LI ,  Lixin YAN ,  Longfei ZHAO

IPC: G06T7/00 ,  G06T11/00

Abstract: A medical image processing apparatus according to an embodiment includes processing circuitry configured: to generate a projection image by implementing an intensity projection on a plurality of two-dimensional images structuring three-dimensional volume data rendering a tubular organ; to obtain a mapping matrix of the intensity projection; to annotate the tubular organ in the projection image; and to identify the tubular organ in the three-dimensional volume data, by inversely mapping the tubular organ annotated in the projection image onto the three-dimensional volume data while using the mapping matrix.