NDLI: MRI brain image classification using neural networks

Content Provider	IEEE Xplore Digital Library
Author	Ibrahim, W.H. Osman, A.A.A. Mohamed, Y.I.
Copyright Year	2013
Description	Author affiliation: Dept. of Med. Eng., Univ. of Sci. & Technol., Khartoum, Sudan (Ibrahim, W.H.; Osman, A.A.A.; Mohamed, Y.I.)
Abstract	Classification of brain tumor using Magnetic resonance Imaging (MRI) is a difficult task due to the variance and complexity of tumors. This paper presents Neural Network techniques for the classification of the magnetic resonance human brain images. The proposed Neural Network technique consists of three stages, preprocessing, dimensionality reduction, and classification. In the first stage, we The MR image will obtain and convert it to data form (encoded information that can be stored, manipulated and transmitted by digital devices), in the second stage have obtained the dimensionally reduction using principles component analysis (PCA), then In the classification stage the Back-Propagation Neural Network has been used as a classifier to classify subjects as normal or abnormal MRI brain images. In the experiment 3×58 datasets of MRI Brain segital images (www.cipr.rpi.edu/resource/sequences/sequence01) have been used for tainting and testing the proposed method. The result of the proposed technique was compared with the results of baseline algorithms, and it presents validity as competitive results quality-wise, and showed that the classification accuracy of our method is 96.33%.
Starting Page	253
Ending Page	258
File Size	653033
Page Count	6
File Format	PDF
e-ISBN	9781467362320
DOI	10.1109/ICCEEE.2013.6633943
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-26
Publisher Place	Sudan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Neurons Linear regression MRI Back-Propagation neural networks Artificial neural networks Vectors Biological neural networks Principal component analysis Brain tumor detection PCA
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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