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

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Abstract

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.
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