Volume 10 Number 6 (Jun. 2015)
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JSW 2015 Vol.10(6): 670-680 ISSN: 1796-217X
doi: 10.17706/jsw.10.6.670-680

Alzheimer’s Disease Image Segmentation with Self-Organizing Map Network

R. Sampath1*, A. Saradha2
1Anna University, Chennai, India.
2Institute of Road Transport and Technology, Erode, Tamil Nadu, India.

Abstract—Detection and segmentation of Alzheimer’s disease (AD) is very important because it provides structural information of abnormal and normal tissues. Functional Magnetic Resonance Imaging (FMRI) is a promising tool for detecting brain image. Alzheimer’s disease (AD) FMRI image segmentation is treated as texture classification problem. In this paper proposed a novel method for AD image segmentation using Self-Organizing Map Network (SOMN). Four different types of features are extracted from the FMRI AD images such as the first order gray level parameters, multi-scale features, textural measures and moment invariant features. These features are used for image segmentation. Application of Adaptive Neuro-Fuzzy Inference System (ANFIS) model utilized for classification of Alzheimer’s disease segmentation image. The proposed Segmentation and classification results are promising.

Index Terms—Alzheimer’s disease (AD), self-organizing map network (SOMN), ANFIS (artificial neural network fuzzy inference system), segmentation.


Cite: R. Sampath, A. Saradha, "Alzheimer’s Disease Image Segmentation with Self-Organizing Map Network," Journal of Software vol. 10, no. 6, pp. 670-680, 2015.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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