Jul 2026· Network Modeling Analysis in Health Informatics and Bioinformatics· Vol 15· 0 citations· 46 references
Computer Science
TL;DR
By integrating boundary-aware segmentation with interpretable quantification, the proposed framework provides an efficient end-to-end tool for cardiac assessment and supporting the evaluation of structural abnormalities such as hypertrophic cardiomyopathy and heart failure.
Cardiac MRE data alone demonstrated the feasibility of accurate LV myocardium segmentation, with nnU-Net and MedSAM both reaching inter-reader-level performance and represent a step toward a self-contained cardiac MRE workflow.
V. Atamaniuk, M. Anders, M. Obrzut et al.· Magnetic Resonance Imaging· 0 citations
A fully supervised framework that couples a Vision Transformer encoder with a convolutional decoder to segment the left ventricle (LV), right ventricle (RV), and myocardium (Myo) on the Automated Cardiac Diagnosis Challenge (ACDC) dataset indicates that transformer-based encoders provide a competitive and interpretable...
Faizan Ahmad, Muhammad Arif Anwar· Journal of Artificial Intell...· 0 citations
Accurate segmentation of cardiac structures in 2D echocardiography is a crucial step for the computation of clinically relevant indices, such as ventricular volumes and ejection fraction (EF). While convolutional neural networks, and in particular UNet-based architectures, have long represented the state of the art for...
Edoardo Bosco, E. Spairani, Francesco Podda et al.· IEEE Access· 0 citations
Echo-DFCNN achieves simultaneous and precise assessment of LVEF and GLS in the study cohorts, demonstrating its potential for robust performance across a wide range of cardiac functions, different image qualities, and machine types.
Zi-Sang Zhang, Ye Zhu, Shu-Jun Chen et al.· PLOS Digital Health· 0 citations
Automated segmentation of the left and right ventricles (LVs and RVs) in cine cardiac MRI (CMR) underpins reliable volumetry and mass estimation. However, papillary muscles and trabeculae (PM/T) introduce clinically meaningful variability and exacerbate cross-dataset domain shift. We present VentrEX, an anatomically gu...
Abla Bedoui, Julieta Anahí Rancati, Ignacio Lugones et al.· Journal of Imaging· 0 citations
Findings from the Myocardial Segmentation with Automated Infarct Quantification (MYOSAIQ) challenge indicate that well-designed UNet-based techniques outperform fully automatic foundation models for LGE MR segmentation.
Olivier Bernard, W. Romero, Cyprien Bouton et al.· 0 citations
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