公开(公告)号：US10573005B2

公开(公告)日：2020-02-25

申请号：US16529769

申请日：2019-08-01

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Xin Wang ,  Youbing Yin ,  Junjie Bai ,  Yi Lu ,  Qi Song ,  Kunlin Cao

IPC: G06T7/11 ,  G06N20/00 ,  G06N3/08 ,  G06T7/174 ,  G06T7/00

Abstract: Embodiments of the disclosure provide systems and methods for analyzing a biomedical image including at least one tree structure object. The system includes a communication interface configured to receive a learning model and a plurality of model inputs derived from the biomedical image. The biomedical image is acquired by an image acquisition device. The system further includes at least one processor configured to apply the learning model to the plurality of model inputs to analyze the biomedical image. The learning model includes a first network configured to process the plurality of model inputs to construct respective feature maps and a second network configured to process the feature maps collectively. The second network is a tree structure network that models a spatial constraint of the tree structure object.

公开(公告)号：US20190325579A1

公开(公告)日：2019-10-24

申请号：US16392516

申请日：2019-04-23

Applicant: SHENZHEN KEYA MEDICAL TECHNOLOGY CORPORATION

Inventor： Xin Wang ,  Youbing Yin ,  Junjie Bai ,  Yi Lu ,  Qi Song

IPC: G06T7/11 ,  G06T7/174 ,  G06T7/00 ,  G06N20/00 ,  G06N3/08

Abstract: Embodiments of the disclosure provide systems and methods for segmenting a biomedical image including at least one tree structure object. The system includes a communication interface configured to receive the biomedical image and a learning model. The biomedical image is acquired by an image acquisition device. The system further includes at least one processor configured to extract a plurality of image patches from the biomedical image and apply the learning model to the plurality of image patches to segment the biomedical image. The learning model includes a convolutional network configured to process the plurality of image patches to construct respective feature maps and a tree structure network configured to process the feature maps collectively to obtain a segmentation mask for the tree structure object. The tree structure network models a spatial constraint of the plurality of image patches.