MRI brain tumor medical images analysis using deep learning techniques: a systematic review

Al-Galal, Sabaa Ahmed Yahya and Alshaikhli, Imad Fakhri Taha and Abdulrazzaq, Mohammed Muayad and UNSPECIFIED (2021) MRI brain tumor medical images analysis using deep learning techniques: a systematic review. Health and Technology Journal, 11. pp. 267-282. ISSN 2190-7188 E-ISSN 2190-7196

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Abstract

The substantial progress of medical imaging technology in the last decade makes it challenging for medical experts and radiologists to analyze and classify. Medical images contain massive information that can be used for diagnosis, surgical planning, training, and research. There is, therefore, a need for a technique that can automatically analyze and classify the images based on their respective contents. Deep Learning (DL) techniques have been recently used for medical image analy- sis, and this paper focuses on DL in the context of analyzing Magnetic Resonance Imaging (MRI) brain medical images. A comprehensive overview of the state-of-the-art processing of brain medical images using deep neural networks is detailed here. The scope of this research paper is restricted to three digital databases: (1) the Science Direct database, (2) the IEEEX- plore Library of Engineering and Technology Technical Literature, and (3) Scopus database. 427 publications were evaluated and discussed in this research paper.

Item Type:	Article (Review)
Additional Information:	6534/89220
Uncontrolled Keywords:	Deep learning · Convolutional neural network · Brain tumor · MRI medical images
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology > Department of Computer Science Kulliyyah of Information and Communication Technology > Department of Computer Science
Depositing User:	Professor Imad Taha
Date Deposited:	12 Apr 2021 15:21
Last Modified:	12 Apr 2021 15:21
URI:	http://irep.iium.edu.my/id/eprint/89220

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