title: Localized components analysis.
abstract: We introduce Localized Components Analysis (LoCA) for describing surface shape variation in an ensemble of biomedical objects using a linear subspace of spatially localized shape components. In contrast to earlier methods, LoCA optimizes explicitly for localized components and allows a flexible trade-off between localized and concise representations. Experiments comparing LoCA to a variety of competing shape representation methods on 2D and 3D shape ensembles establish the superior ability of LoCA to modulate the locality-conciseness tradeoff and generate shape components corresponding to intuitive modes of shape variation. Our formulation of locality in terms of compatibility between pairs of surface points is shown to be flexible enough to enable spatially-localized shape descriptions with attractive higher-order properties such as spatial symmetry.
authors.affiliation: Computer Science, University of California, Davis, USA.
authors.forename: Dan
authors.initials: D
authors.lastname: Alcantara
authors.forename: Owen
authors.initials: O
authors.lastname: Carmichael
authors.forename: Eric
authors.initials: E
authors.lastname: Delson
authors.forename: Will
authors.initials: W
authors.lastname: Harcourt-Smith
authors.forename: Kirsten
authors.initials: K
authors.lastname: Sterner
authors.forename: Stephen
authors.initials: S
authors.lastname: Frost
authors.forename: Rebecca
authors.initials: R
authors.lastname: Dutton
authors.forename: Paul
authors.initials: P
authors.lastname: Thompson
authors.forename: Howard
authors.initials: H
authors.lastname: Aizenstein
authors.forename: Oscar
authors.initials: O
authors.lastname: Lopez
authors.forename: James
authors.initials: J
authors.lastname: Becker
authors.forename: Nina
authors.initials: N
authors.lastname: Amenta
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003337:Corpus Callosum / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity