公开(公告)号：US20230281806A1

公开(公告)日：2023-09-07

申请号：US18115726

申请日：2023-02-28

Applicant: Henan University of Science and Technology

Inventor： Mingchuan ZHANG ,  Mengjie GU ,  Lin WANG ,  Qingtao WU ,  Junlong ZHU ,  Zhihang JI

IPC: G06T7/00 ,  G06T5/00 ,  G06T5/50 ,  G06T7/11 ,  G06V10/25 ,  G06V10/44 ,  G06V10/764

CPC classification number: G06T7/0012 ,  G06T5/002 ,  G06T5/50 ,  G06T7/11 ,  G06V10/25 ,  G06V10/44 ,  G06V10/764 ,  G06T2207/10132 ,  G06T2207/20084 ,  G06T2207/20221 ,  G06T2207/30048 ,  G06T2207/30242

Abstract: A microbubble counting method for patent foramen ovale (PFO) based on deep learning is provided. The method includes: segmenting a target area of a left heart in an ultrasonic image; and generating a corresponding density map for a segmented target image using a convolutional neural network (CNN), and calculating a total number of the microbubbles in the segmented area by integration and summation. The method has the following beneficial effects: target segmentation is performed on the left atrium and left ventricular area of the heart using the neural network, and effective segmentation of the target area of the left heart is the key of obtaining parameters such as a size and form of the target area. The target area is quantitatively analyzed according to a segmentation result, and the number of the microbubbles in the target area is counted.