Automatic brain MR images diagnosis based on edge fractal dimension and spectral energy signature.
A new automatic system to detect pathologies in human brain magnetic resonance (MR) images is presented. The goal is to classify normal versus abnormal images affected by Alzheimer, Glioma, Herpes, Metastatic, and Multiple Sclerosis. The extracted features are the fractal dimension of edges in the Hilbert domain, and the skewness and kurtosis of their spectral energy distribution. The proposed system (FDSE) outperforms the popular discrete wavelet transform (DWT) and principal component analysis (PCA).
Department of Computer Science, University of Quebec at Montreal, Montreal, Quebec, Canada. lahmiri.salim@courrier.uqam.ca
Salim
S
Lahmiri
Mounir
M
Boukadoum
D001331:Automation; D001927:Brain Diseases / Q000175:diagnosis*; D017709:Fractals; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*