Tag: Deep learning

A Two-stage Method with a Shared 3D U-Net for Left Atrial Segmentation of Late Gadolinium-Enhanced MRI Images

Announcing a new article publication for Cardiovascular Innovations and Applications journal.     Studying atrial structure directly is crucial for comprehending and managing atrial fibrillation (AF). Accurate reconstruction and measurement of atrial geometry for clinical purposes remains challenging, despite potential improvements in the visibility of AF-associated structures with late gadolinium-enhanced magnetic resonance imaging. This difficulty arises from the varying intensities caused by increased tissue enhancement and artifacts, as well as variability in image quality. Therefore, an efficient algorithm for fully automatic 3D left atrial segmentation is proposed in this study.

https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2023.0039

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Jieyun Bai, Ruiyu Qiu and Jianyu Chen et al. A Two-stage Method with a Shared 3D U-Net for Left Atrial Segmentation of Late Gadolinium-Enhanced MRI Images. CVIA. 2023. Vol. 8(1). DOI: 10.15212/CVIA.2023.0039

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