Research Area:  Machine Learning

Abstract:

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.

Keywords:  

Author(s) Name:  Lu Liu1, Jelmer M Wolterink, Christoph Brune and Raymond N J Veldhuis

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