Deep learning applications in medical image analysis
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, foc...
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sg-ntu-dr.10356-875922020-03-07T13:57:31Z Deep learning applications in medical image analysis Ker, Justin Wang, Lipo. Rao, Jai Lim, Tchoyoson School of Electrical and Electronic Engineering Medical Image Analysis Convolutional Neural Networks 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. Published version 2018-08-06T04:26:29Z 2019-12-06T16:45:12Z 2018-08-06T04:26:29Z 2019-12-06T16:45:12Z 2018 Journal Article Ker, J., Wang, L., Rao, J., & Lim, T. (2018). Deep learning applications in medical image analysis. IEEE Access, 6, 9375-9389. https://hdl.handle.net/10356/87592 http://hdl.handle.net/10220/45462 10.1109/ACCESS.2017.2788044 en IEEE Access © 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 15 p. application/pdf |
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Medical Image Analysis Convolutional Neural Networks |
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Medical Image Analysis Convolutional Neural Networks Ker, Justin Wang, Lipo. Rao, Jai Lim, Tchoyoson Deep learning applications in medical image analysis |
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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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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Ker, Justin Wang, Lipo. Rao, Jai Lim, Tchoyoson |
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Article |
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Ker, Justin Wang, Lipo. Rao, Jai Lim, Tchoyoson |
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Ker, Justin |
title |
Deep learning applications in medical image analysis |
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Deep learning applications in medical image analysis |
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Deep learning applications in medical image analysis |
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Deep learning applications in medical image analysis |
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Deep learning applications in medical image analysis |
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deep learning applications in medical image analysis |
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2018 |
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https://hdl.handle.net/10356/87592 http://hdl.handle.net/10220/45462 |
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1681038285271465984 |