Please use this identifier to cite or link to this item:
Title: Deep learning applications in medical image analysis
Authors: Ker, Justin
Wang, Lipo.
Rao, Jai
Lim, Tchoyoson
Keywords: Medical Image Analysis
Convolutional Neural Networks
Issue Date: 2018
Source: Ker, J., Wang, L., Rao, J., & Lim, T. (2018). Deep learning applications in medical image analysis. IEEE Access, 6, 9375-9389.
Series/Report no.: IEEE Access
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.
DOI: 10.1109/ACCESS.2017.2788044
Rights: © 2017 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See for more information.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

Files in This Item:
File Description SizeFormat 
Deep learning applications in medical image analysis.pdf6.05 MBAdobe PDFThumbnail

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.