Anatomy-aided deep learning for medical image segmentation: a review

• Published in: Physics in medicine & biology 2021-06, Vol.66 (11), p.11
• Main Authors: Liu, Lu, Wolterink, Jelmer M, Brune, Christoph, Veldhuis, Raymond N J
• Format: Article
• Language: English
• Subjects: anatomical information; deep learning; medical image segmentation
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/1361-6560/abfbf4

Deep learning has become widely used for medical image segmentation in recent years. However, despite these advances, there are still problems for which deep learning-based segmentation fails. Recently, some deep learning approaches had a breakthrough by using anatomical information which is the crucial cue for manual segmentation. In this paper, we provide a review of anatomy-aided deep learning for medical image segmentation which covers systematically summarized anatomical information categories and corresponding representation methods. We address known and potentially solvable challenges in anatomy-aided deep learning and present a categorized methodology overview on using anatomical information with deep learning from over 70 papers. Finally, we discuss the strengths and limitations of the current anatomy-aided deep learning approaches and suggest potential future work.