Journal of Shandong University (Health Sciences) ›› 2024, Vol. 62 ›› Issue (9): 66-73.doi: 10.6040/j.issn.1671-7554.0.2024.0317

• Advances in Basic and Clinical Research on Aortic Diseases-Research Progress • Previous Articles    

Research progress of deep learning in automatic segmentation of aortic images

TANG Yuning, PAN Tianyue, DONG Zhihui, FU Weiguo   

  1. Department of Vascular Surgery, Zhongshan Hospital of Fudan University, Shanghai 200032, China
  • Published:2024-10-10

Abstract: In the field of medical image processing, accurate image segmentation is crucial for the diagnosis and treatment planning of aortic diseases. Deep learning techniques, especially convolutional neural networks, have made significant progress in medical image segmentation tasks in recent years. This article reviewed the research on the application of deep learning models to the automatic segmentation of aortic lesion images, summarized the contributions of these current techniques to improving the segmentation accuracy and efficiency, and discussed the challenges faced by existing methods and more possibilities and directions for future research.

Key words: Deep learning, Aortic image segmentation, Convolutional neural networks, Aortic disease, Computer vision

CLC Number: 

  • R543.1
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