FUZZY C-MEANS CLUSTERING AND PRINCIPAL COMPONENT ANALYSIS OF TIME-SERIES FROM NEAR-INFRARED IMAGING OF FOREARM ISCHEMIA

Fuzzy C-means clustering and principal components analysis were used t o analyze a temporal series of near-IR images taken of a human forearm during periods of venous outflow restriction and complete forearm isc hemia. The principal component eigen-time course analysis provided no useful information and the principal component eigen-image analysis ga ve results that correlated poorly with anatomical features. The fuzzy C-means clustering analysis, on the other hand, showed distinct region al differences in the hemodynamic response and scattering properties o f the tissue, which correlated well with the anatomical features of th e forearm. (C) 1997 Elsevier Science Ltd.