Semi-supervised cluster analysis of imaging data

• Published in: NeuroImage (Orlando, Fla.) Vol. 54; no. 3; pp. 2185 - 2197
• Main Authors: Filipovych, Roman, Resnick, Susan M., Davatzikos, Christos
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.02.2011; Elsevier Limited
• Subjects: Aged; Aged, 80 and over; Aging; Algorithms; Artificial Intelligence; Atrophy; Brain - pathology; Classification; Cluster Analysis; Cognition - physiology; Cognitive ability; Computer Simulation; Disease; Humans; Image Processing, Computer-Assisted - statistics & numerical data; Longitudinal Studies; Magnetic Resonance Imaging - methods; MCI; Middle Aged; Models, Neurological; MRI; Neighborhoods; Neuropsychological Tests; Older people; Pathology; Patients; Principal Component Analysis; Semi-supervised pattern analysis; Studies; Cluster analysis; Aging; Semi-supervised pattern analysis; MCI; MRI

In this paper, we present a semi-supervised clustering-based framework for discovering coherent subpopulations in heterogeneous image sets. Our approach involves limited supervision in the form of labeled instances from two distributions that reflect a rough guess about subspace of features that are...