Prospects of deep learning for medical imaging

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Title
Prospects of deep learning for medical imaging
Author(s)
Jonghoon Kim; Jisu Hong; Hyunjin Park
Publication Date
2018-06
Journal
Precision and Future Medicine, v.2, no.2, pp.37 - 52
Publisher
SUNGKYUNKWAN UNIVERSITY SCHOOL OF MEDICINE
Abstract
Machine learning techniques are essential components of medical imaging research. Recently, a highly flexible machine learning approach known as deep learning has emerged as a disruptive technology to enhance the performance of existing machine learning techniques and to solve previously intractable problems. Medical imaging has been identified as one of the key research fields where deep learning can contribute significantly. This review article aims to survey deep learning literature in medical imaging and describe its potential for future medical imaging research. First, an overview of how traditional machine learning evolved to deep learning is provided. Second, a survey of the application of deep learning in medical imaging research is given. Third, wellknown software tools for deep learning are reviewed. Finally, conclusions with limitations and future directions of deep learning in medical imaging are provided Copyright © 2018 Sungkyunkwan
URI
https://pr.ibs.re.kr/handle/8788114/5466
ISSN
2508-7940
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > Journal Papers (저널논문)
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