ArticleMedical image analysis2018
Algorithms for left atrial wall segmentation and thickness - Evaluation on an open-source CT and MRI image database.
Article in Medical image analysis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical image analysis on left atrial LGE MRI for atrial fibrillation studies: A review.Medical image analysis · 2022Pooled it
- Multimodal Characterization of Atrial Fibrillation: From Patient-Specific Anatomy and Electrophysiology to Standardized Atrial Mapping.Tomography (Ann Arbor, Mich.) · 2026Review
- HeartSimSage: Attention-Enhanced Graph Neural Networks for Accelerating Cardiac Mechanics Modeling.Journal of computational physics · 2026Article
- Effects of Left Atrial Wall Thickness on Myocardial Mechanics and Blood Dynamics using Multiscale Modeling.bioRxiv : the preprint server for biology · 2026Article
- Segmental analysis of left atrial substrate severity predictors in patients undergoing persistent atrial fibrillation ablation.Frontiers in cardiovascular medicine · 2026Article
- A three-dimensional computational study of critical pressures of dissection propagation in the aorta.Biomechanics and modeling in mechanobiology · 2025Article
- Utilizing multimodal artificial intelligence to advance cardiovascular diseases.Precision clinical medicine · 2025Review
- Automatic Bi-Atrial Segmentation and Biomarker Extraction from Late Gadolinium-Enhanced MRI Using Deep Learning.Expert systems with applications · 2025Article
- On preserving anatomical detail in statistical shape analysis for clustering: focus on left atrial appendage morphology.Frontiers in network physiology · 2024Article
- Posterior wall thickness of the confluent inferior pulmonary veins measured by left atrial intracardiac echocardiography: implications for catheter ablation.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2024Article
- Chamber-specific wall thickness features in human atrial fibrillation.Interface focus · 2023Article
- Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease.Biophysics reviews · 2023Review
- Real-time visualization of the esophagus and left atrial posterior wall by intra-left atrial echocardiography.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2022Article
- Extent of Left Atrial Fibrosis Correlates with Descending Aorta Proximity at 3D Late Gadolinium Enhancement Cardiac MRI in Patients with Atrial Fibrillation.Radiology. Cardiothoracic imaging · 2022Article
- A deep-learning approach for direct whole-heart mesh reconstruction.Medical image analysis · 2021Article
- Machine Learning-Derived Fractal Features of Shape and Texture of the Left Atrium and Pulmonary Veins From Cardiac Computed Tomography Scans Are Associated With Risk of Recurrence of Atrial Fibrillation Postablation.Circulation. Arrhythmia and electrophysiology · 2021Article
- Atrial scar quantification via multi-scale CNN in the graph-cuts framework.Medical image analysis · 2020Article
- Deep Learning for Cardiac Image Segmentation: A Review.Frontiers in cardiovascular medicine · 2020Review
- Simultaneous Multi-Structure Segmentation of the Heart and Peripheral Tissues in Contrast Enhanced Cardiac Computed Tomography Angiography.IEEE access : practical innovations, open solutions · 2020Article
- Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.Medical image analysis · 2019Article
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Authors and funding
19 authors.
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Abstract
Structural changes to the wall of the left atrium are known to occur with conditions that predispose to Atrial fibrillation. Imaging studies have demonstrated that these changes may be detected non-invasively. An important indicator of this structural change is the wall's thickness. Present studies have commonly measured the wall thickness at few discrete locations. Dense measurements with computer algorithms may be possible on cardiac scans of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). The task is challenging as the atrial wall is a thin tissue and the imaging resolution is a limiting factor. It is unclear how accurate algorithms may get and how they compare in this new emerging area. We approached this problem of comparability with the Segmentation of Left Atrial Wall for Thickness (SLAWT) challenge organised in conjunction with MICCAI 2016 conference. This manuscript presents the algorithms that had participated and evaluation strategies for comparing them on the challenge image database that is now open-source. The image database consisted of cardiac CT (n=10) and MRI (n=10) of healthy and diseased subjects. A total of 6 algorithms were evaluated with different metrics, with 3 algorithms in each modality. Segmentation of the wall with algorithms was found to be feasible in both modalities. There was generally a lack of accuracy in the algorithms and inter-rater differences showed that algorithms could do better. Benchmarks were determined and algorithms were ranked to allow future algorithms to be ranked alongside the state-of-the-art techniques presented in this work. A mean atlas was also constructed from both modalities to illustrate the variation in thickness within this small cohort.
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