Title :
Detection and classification of MS using magnetisation transfer ratio images
Author :
Dehmeshki, J. ; Ruto, A.C. ; Parker, G.J.M. ; Arridge, S. ; Miller, D.H. ; Tofts, P.S.
Author_Institution :
Dept. of Clinical Neurol., Univ. Coll. London, UK
Abstract :
Principal component (PCA) and multiple discriminant analysis (MDA) are applied to magnetization transfer ratio (MTR) images in multiple sclerosis (MS). PCA and MDA are used to characterise subtle diffuse changes in MS. PCA is applied to MTR histograms to identify regions of significant variation. These areas are indicated as possible lesion areas. We compare two classifiers to recognise differences between normal controls and different types of MS disease; a Bayesian classifier is trained in PC space, and the histogram space is transformed to the optimal discriminant space for a nearest neighbor classifier
Keywords :
Bayes methods; biomagnetism; diseases; image classification; magnetisation; medical image processing; principal component analysis; Bayesian classifier; MDA; MS; MTR images; PCA; diffuse changes; histogram space; lesion areas; magnetisation transfer ratio images; multiple discriminant analysis; multiple sclerosis; nearest neighbor classifier; optimal discriminant space; principal component analysis; Bayesian methods; Diseases; Histograms; Image analysis; Lesions; Magnetic analysis; Magnetization; Multiple sclerosis; Optimal control; Principal component analysis;
Conference_Titel :
Image and Signal Processing and Analysis, 2000. IWISPA 2000. Proceedings of the First International Workshop on
Conference_Location :
Pula
Print_ISBN :
953-96769-2-4
DOI :
10.1109/ISPA.2000.914902