BROWSE

Related Scientist

cnir's photo.

cnir
뇌과학이미징연구단
more info

ITEM VIEW & DOWNLOAD

Prospects of deep learning for medical imaging

Cited 0 time in webofscience Cited 0 time in scopus
3,047 Viewed 1,883 Downloaded
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
DOI
10.23838/pfm.2018.00030
ISSN
2508-7940
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
Files in This Item:
49_박현진_Prospects of deep learning for medical imaging.pdfDownload

qrcode

  • facebook

    twitter

  • Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
해당 아이템을 이메일로 공유하기 원하시면 인증을 거치시기 바랍니다.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse