Left Atrial and Scar Quantification and Segmentation: First Challenge, LAScarQS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings

Zhuang, Xiahai, Li, Lei, Wang, Sihan and Wu, Fuping (eds.) (2023) Left Atrial and Scar Quantification and Segmentation: First Challenge, LAScarQS 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13586), vol. 13586, Springer Cham, 164pp.

Abstract

The proceedings contain 15 papers. The special focus in this conference is on Left Atrial and Scar Quantification and Segmentation Challenge. The topics include: Multi-depth Boundary-Aware Left Atrial Scar Segmentation Network; self Pre-training with Single-Scale Adapter for Left Atrial Segmentation; UGformer for Robust Left Atrium and Scar Segmentation Across Scanners; Automatically Segment the Left Atrium and Scars from LGE-MRIs Using a Boundary-Focused nnU-Net; two Stage of Histogram Matching Augmentation for Domain Generalization: Application to Left Atrial Segmentation; sequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Network and Boundary-Based Processing; LA-HRNet: High-Resolution Network for Automatic Left Atrial Segmentation in Multi-center LEG MRI; Edge-Enhanced Feature Guided Joint Segmentation of Left Atrial and Scars in LGE MRI Images; preface; LASSNet: A Four Steps Deep Neural Network for Left Atrial Segmentation and Scar Quantification; TESSLA: Two-Stage Ensemble Scar Segmentation for the Left Atrium; deep U-Net Architecture with Curriculum Learning for Left Atrial Segmentation; cross-Domain Segmentation of Left Atrium Based on Multi-scale Decision Level Fusion.

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Contributors

Editor: Lei Li

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