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Volume & Issue no: Volume 3, Issue 12, December 2014

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Title:
NMF-SVM Based CAD Tool for the Diagnosis of Alzheimers Disease
Author Name:
Ms. Tejal A. Fuse, Mr. Nikita D. Jayasignpure and Prof. Pragati D. Pawar
Abstract:
ABSTRACT This paper presents a novel computer-aided diagnosis (CAD) technique for the early diagnosis of the Alzheimer’s disease (AD) based on non-negative matrix factorization (NMF) and support vector machines (SVM) with bounds of confidence. For the study and classification of functional brain images the CAD tool is designed. For this purpose, two brain image databases are selected first one : a single photon emission computed tomography (SPECT) database and second is positron emission tomography (PET) images, both of them containing data for both Alzheimer’s disease (AD) patients and healthy controls. The Fisher discriminant ratio (FDR) and nonnegative matrix factorization (NMF) are used for feature selection and extraction of the most relevant features. The NMF-transformed sets of data are classified by means of a SVM-based classifier with bounds of confidence for decision. The proposed NMF-SVM method gives classification accuracy up to 91% with high sensitivity and specificity rates.
Cite this article:
Ms. Tejal A. Fuse, Mr. Nikita D. Jayasignpure and Prof. Pragati D. Pawar , " NMF-SVM Based CAD Tool for the Diagnosis of Alzheimers Disease" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 3, Issue 12, December 2014 , pp. 268-274 , ISSN 2319 - 4847.
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