Automated detection of glioblastoma tumor in brain magnetic imaging using ANFIS classifier-Reference-Cited by-同舟云学术

Automated detection of glioblastoma tumor in brain magnetic imaging using ANFIS classifier

Published:2016-06 Issue:2 Volume:26 Page:151-156
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int. J. Imaging Syst. Technol.

Author:

Thirumurugan P.¹,Ramkumar D.²,Batri K.¹¹,Siva Sundhara Raja D.³

Affiliation:

1. Department of Electronics and Communication Engineering; PSNA College of Engineering and Technology; India

2. Department of Electronics and Communication Engineering; Bharat Niketan Engineering College; Theni India

3. Department of Electronics and Communication Engineering; SACS MAVMM Engineering College; India

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Reference10 articles.

1. Automated Feature Extraction in Brain Tumor by Magnetic Resonance Imaging Using Gaussian Mixture Models;Chaddad;Int J Biomed Imaging,2015

2. Gutman, Integrative, Multimodal Analysis of Glioblastoma Using TCGA Molecular Data, Pathology Images, and Clinical Outcomes;Kong;IEEE Trans Biomed Eng,2011

3. Multi-class abnormal brain tissue segmentation using texture features;Reza;Proc NCI MICCAI-BRATS,2013

4. In-Depth Analysis and Evaluation of Diffusive Glioma Models;Roniotis;IEEE Trans Inf Technol Biomed,2012

5. Towards a Computer Aided Prognosis for Brain Glioblastomas Tumor Growth Estimation;Sallemi;IEEE Trans Nanobiosci,2015

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