Research progress of automatic segmentation of left atrial CTA image based on deep learning

Corresponding author: chen hui, ch2xf@163.com

DOI: 10.12201/bmr.202503.00042

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  Abstract: Abstract: Purpose/Significance To explore the application of deep learning technology in automatic segmentation of left atrial CTA images. By reviewing the relevant theoretical framework and research status at home and abroad, some future research directions were found.Method/Process The related articles at home and abroad were searched to analyze the traditional segmentation methods of left atrial image and the segmentation methods based on deep learning, and the effect was evaluated.Result/Conclusion Deep learning technology has made significant progress in left atrial image segmentation, which provides strong support for clinical diagnosis and treatment. However, there are still research gaps that need to be filled. This paper provides a reference for exploring and improving the research and application of automatic left atrial image segmentation based on deep learning.

  Key words: deep learning (DL)； left atrium segmentation； artificial intelligence (AI)； atrial fibrillation (AF)；computed Tomography Angiography（CTA）

  Submit time: 14 March 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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