ROmuvVAppDeVOW5bxTLxNgAjtFEj2XhOpKgEPwqVNT54DYfN6AakdKSYJRX2
Current position: Home >> Scientific Research >> Paper Publications

MCAL: An Anatomical Knowledge Learning Model for Myocardial Segmentation in 2-D Echocardiography

Hits:

Institution:信息科学与工程学院

Title of Paper:MCAL: An Anatomical Knowledge Learning Model for Myocardial Segmentation in 2-D Echocardiography

Journal:IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control

Key Words:Boundary distance transform weight (BDTW);multiconstrained aggregate learning (MCAL);myocardial segmentation

First Author:崔笑笑

Document Code:1539148676301119489

Volume:69

Issue:4

Page Number:1277-1287

Number of Words:6

Translation or Not:No

Date of Publication:2022-04

Release Time:2022-12-24

Prev One:Weak lesion feature extraction by dual-branch separation and enhancement network for safe hemorrhagic transformation prediction

Next One:BMRMIA: A Platform for Radiologists to Systematically Learn Automated Medical Image Analysis by Three Dimensional Medical Decision Support System