EFNet: A multitask deep learning network for simultaneous quantification of left ventricle structure and function.
Journal:
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PMID:
39208517
Abstract
PURPOSE: The purpose of this study is to develop an automated method using deep learning for the reliable and precise quantification of left ventricle structure and function from echocardiogram videos, eliminating the need to identify end-systolic and end-diastolic frames. This addresses the variability and potential inaccuracies associated with manual quantification, aiming to improve the diagnosis and management of cardiovascular conditions.