Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture.
Journal:
Biomedical physics & engineering express
Published Date:
Feb 18, 2020
Abstract
BACKGROUND: Magnetic resonance cine imaging is the accepted standard for cardiac functional assessment. Left ventricular (LV) segmentation plays a key role in volumetric functional quantification of the heart. Conventional manual analysis is time-consuming and observer-dependent. Automated segmentation approaches are needed to improve the clinical workflow of cardiac functional quantification. Recently, deep-learning networks have shown promise for efficient LV segmentation.