On the number of clusters and the fuzziness index for unsupervised FCA application to BOLD fMRI time series

• Published in: Medical image analysis Vol. 5; no. 1; pp. 55 - 67
• Main Authors: Fadili, M.J, Ruan, S, Bloyet, D, Mazoyer, B
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.03.2001; Elsevier
• Subjects: Algorithms; Brain - anatomy & histology; Brain Mapping - methods; Cluster Analysis; Computer Science; fMRI; Fuzziness index; Fuzzy Logic; Humans; Image Processing; Magnetic Resonance Imaging - methods; Phantoms, Imaging; ROC; UFCA; Validity measure; VF: Validity Function; CNR: Contrast-to-Noise Ratio; Validity measure; ROC; UFCA; fMRI; fMRI: functional Magnetic Resonance Imaging; FCM: Fuzzy c-means; ROC: Receiver Operating Characteristics; FCA: Fuzzy Clustering Analysis; Fuzziness index; UFCA: Unsupervised Fuzzy Clustering Analysis; MF: Membership Function; MDM: Membership Degree Map

The aim of this paper is to present an exploratory data-driven strategy based on Unsupervised Fuzzy Clustering Analysis (UFCA) and its potential for fMRI data analysis in the temporal domain. The a priori definition of the number of clusters is addressed and solved using heuristics. An original vali...