Alzheimer’s Disease Detection in Brain Magnetic Resonance Images Using Multiscale Fractal Analysis

Lahmiri, Salim et Boukadoum, Mounir (2013). « Alzheimer’s Disease Detection in Brain Magnetic Resonance Images Using Multiscale Fractal Analysis ». ISRN Radiology, 2013, pp. 1-7.

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Résumé

We present a new automated system for the detection of brain magnetic resonance images (MRI) affected by Alzheimer’s disease (AD).The MRI is analyzed by means of multiscale analysis (MSA) to obtain its fractals at six different scales. The extracted fractals are used as features to differentiate healthy brain MRI from those of AD by a support vector machine (SVM) classifier.The result of classifying 93 brain MRIs consisting of 51 images of healthy brains and 42 of brains affected by AD, using leave-one-out crossvalidation method, yielded 99.18% ± 0.01 classification accuracy, 100% sensitivity, and 98.20% ± 0.02 specificity. These results and a processing time of 5.64 seconds indicate that the proposed approach may be an efficient diagnostic aid for radiologists in the screening for AD.

Type:	Article de revue scientifique
Mots-clés ou Sujets:	brain magnetic resonance images (MRI), Alzheimer’s disease, vector machine (SVM) classifier
Unité d'appartenance:	Faculté des sciences > Département d'informatique
Déposé par:	A. Mounir Boukadoum
Date de dépôt:	10 mai 2016 13:09
Dernière modification:	30 mai 2016 14:47
Adresse URL :	http://archipel.uqam.ca/id/eprint/8435

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