Research Area:  Machine Learning
Deep learning (DL) has become widely used for medical image segmentation in recent years. However, despite these advances, there are still problems for which DL-based segmentation fails. Recently, some DL 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 DL 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 DL and present a categorized methodology overview on using anatomical information with DL from over 70 papers. Finally, we discuss the strengths and limitations of the current anatomy-aided DL approaches and suggest potential future work.
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Author(s) Name:  Lu Liu1, Jelmer M Wolterink, Christoph Brune and Raymond N J Veldhuis
Journal name:  Physics in Medicine & Biology
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Publisher name:  IOP Science
DOI:  10.1088/1361-6560/abfbf4
Volume Information:  Volume 66, Number 11
Paper Link:   https://iopscience.iop.org/article/10.1088/1361-6560/abfbf4/meta