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Journal of Imaging Informatics in Medicine

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Open Access 01-08-2019

Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges

Authors: Mohammad Hesam Hesamian, Wenjing Jia, Xiangjian He, Paul Kennedy

Published in: Journal of Imaging Informatics in Medicine | Issue 4/2019

Abstract

Deep learning-based image segmentation is by now firmly established as a robust tool in image segmentation. It has been widely used to separate homogeneous areas as the first and critical component of diagnosis and treatment pipeline. In this article, we present a critical appraisal of popular methods that have employed deep-learning techniques for medical image segmentation. Moreover, we summarize the most common challenges incurred and suggest possible solutions.

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Title: Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges
Authors: Mohammad Hesam Hesamian
Wenjing Jia
Xiangjian He
Paul Kennedy
Publication date: 01-08-2019
Publisher: Springer International Publishing
Published in: Journal of Imaging Informatics in Medicine / Issue 4/2019
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI: https://doi.org/10.1007/s10278-019-00227-x

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Deep Learning Techniques for Medical Image Segmentation: Achievements and Challenges

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