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Deep Learning Applications in Medical Image Analysis

Open access
Ker, Justin, Wang, Lipo, Rao, Jai, Lim, Tchoyoson·2018·IEEE Access
DOI 10.1109/access.2017.2788044
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Abstract

The tremendous success of machine learning algorithms at image recognition tasks in recent years intersects with a time of dramatically increased use of electronic medical records and diagnostic imaging. This review introduces the machine learning algorithms as applied to medical image analysis, focusing on convolutional neural networks, and emphasizing clinical aspects of the field. The advantage of machine learning in an era of medical big data is that significant hierarchal relationships within the data can be discovered algorithmically without laborious hand-crafting of features. We cover key research areas and applications of medical image classification, localization, detection, segmentation, and registration. We conclude by discussing research obstacles, emerging trends, and possible future directions.

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Metadata

Authors
Ker, J., Wang, L., Rao, J., & Lim, T.
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2018
Volume
6
Pages
9375-9389
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2017.2788044
OpenAlex
W2777186991
Cited by
1,481
References
50
FWCI
39.65
Type
journal article
Language
en
Open access
gold
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/OAPA.html (vor)
Funders
National Neuroscience Institute–Nanyang Technological University Neurotechnology Fellowship

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CoChat. (2026). Citation check: Deep Learning Applications in Medical Image Analysis. https://app.cochat.ai/papers/10.1109/access.2017.2788044
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Ker, J., Wang, L., Rao, J., & Lim, T. (2018). Deep Learning Applications in Medical Image Analysis. IEEE Access. https://doi.org/10.1109/access.2017.2788044

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