AWSnet: An auto-weighted supervision attention network for myocardial scar and edema segmentation in multi-sequence cardiac magnetic resonance images

KN Wang, X Yang, J Miao, L Li, J Yao, P Zhou… - Medical Image …, 2022 - Elsevier
Multi-sequence cardiac magnetic resonance (CMR) provides essential pathology
information (scar and edema) to diagnose myocardial infarction. However, automatic …

[HTML][HTML] Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging—A systematic review

N Jathanna, A Podlasek, A Sokol, D Auer… - … digital health journal, 2021 - Elsevier
Background Accurate, rapid quantification of ventricular scar using cardiac magnetic
resonance imaging (CMR) carries importance in arrhythmia management and patient …

Multi-sequence myocardium segmentation with cross-constrained shape and neural network-based initialization

J Liu, H Xie, S Zhang, L Gu - Computerized Medical Imaging and Graphics, 2019 - Elsevier
For myocardial infarction (MI) patients, delayed enhancement (DE) and T2-weighted
cardiovascular magnetic resonance imaging (CMR) can play significant roles in diagnosis …

Myocardial fibrosis delineation in late gadolinium enhancement images of Hypertrophic Cardiomyopathy patients using deep learning methods.

M Langarizadeh, M Jahanshahi - Journal of Health …, 2022 - search.ebscohost.com
Introduction: Accurate delineation of myocardial fibrosis in Late Gadolinium Enhancement
on Cardiac Magnetic Resonance (LGE-CMR) has a crucial role in the assessment and risk …

Left ventricle segmentation using a Bayesian approach with distance dependent shape priors

R Cardenas, AH Curiale, G Mato - Biomedical Physics & …, 2020 - iopscience.iop.org
We propose a method for segmentation of the left ventricle in magnetic resonance cardiac
images. The framework consists of an initial Bayesian segmentation of the central slice of …