Multicentre Bi-atrial Segmentation from LGE-MRI for Atrial Fibrillation with a 2D and 3D Framework

arXiv:2609.22398 · eess.IV, cs.CV · Submitted 2026-09-18 · Read on arXiv

eess.IV, cs.CV

Submitted: 2026-09-18

Updated: 2026-09-18

Terminology

• Accuracy — 17× in this paper · explained in 1 episode
• Ablation — 13× in this paper · explained in 1 episode
• Domain Shift — 13× in this paper · explained in 4 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Benchmarking — 11× in this paper · explained in 3 episodes
• Fine-Tuning — 9× in this paper · explained in 5 episodes
• Adaptation — 8× in this paper · explained in 1 episode
• nnU-Net — 8× in this paper · explained in 2 episodes
• Robustness — 7× in this paper · explained in 5 episodes
• Clustering — 6× in this paper · explained in 2 episodes
• Domain Adaptation — 6× in this paper · explained in 5 episodes
• Right Atria — 6× in this paper
• Left Atria — 5× in this paper
• Average Surface Distance — 4× in this paper
• Dice Similarity Coefficient — 4× in this paper
• Transformer — 4× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Distribution Shift — 3× in this paper · explained in 5 episodes
• Regression Coefficient — 3× in this paper
• Root Mean Squared Error — 3× in this paper
• Segmentation Masks — 3× in this paper · explained in 2 episodes
• Transferability — 3× in this paper · explained in 4 episodes
• U-net architecture — 3× in this paper · explained in 3 episodes
• Mean Absolute Error — 2× in this paper
• Alignment — 1× in this paper · explained in 1 episode
• Anisotropy — 1× in this paper · explained in 3 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Data Heterogeneity — 1× in this paper · explained in 3 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• External Validation — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Parsimony — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Two-Stage Framework — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Integrating Deep Learning in Cardiology: A Comprehensive Review of Atrial Fibrillation, Left Atrial Scar Segmentation, and the Frontiers of State-of-the-Art Techniques
• SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
• UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
• How good nnU-Net for Segmenting Cardiac MRI: A Comprehensive Evaluation
• LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation
• Customized Segment Anything Model for Medical Image Segmentation
• U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation

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