title: Multiscale deformable model segmentation and statistical shape analysis using medial descriptions.
abstract: This paper presents a multiscale framework based on a medial representation for the segmentation and shape characterization of anatomical objects in medical imagery. The segmentation procedure is based on a Bayesian deformable templates methodology in which the prior information about the geometry and shape of anatomical objects is incorporated via the construction of exemplary templates. The anatomical variability is accommodated in the Bayesian framework by defining probabilistic transformations on these templates. The transformations, thus, defined are parameterized directly in terms of natural shape operations, such as growth and bending, and their locations. A preliminary validation study of the segmentation procedure is presented. We also present a novel statistical shape analysis approach based on the medial descriptions that examines shape via separate intuitive categories, such as global variability at the coarse scale and localized variability at the fine scale. We show that the method can be used to statistically describe shape variability in intuitive terms such as growing and bending.
authors.affiliation: Medical Image Display and Analysis Group, University of North Carolina at Chapel Hill, 27514, USA. joshi@radonc.unc.edu
authors.forename: Sarang
authors.initials: S
authors.lastname: Joshi
authors.forename: Stephen
authors.initials: S
authors.lastname: Pizer
authors.forename: P Thomas
authors.initials: PT
authors.lastname: Fletcher
authors.forename: Paul
authors.initials: P
authors.lastname: Yushkevich
authors.forename: Andrew
authors.initials: A
authors.lastname: Thall
authors.forename: J S
authors.initials: JS
authors.lastname: Marron
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003337:Corpus Callosum / Q000000981:diagnostic imaging; D004548:Elasticity; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007668:Kidney / Q000000981:diagnostic imaging; D007680:Kidney Neoplasms / Q000000981:diagnostic imaging; D008954:Models, Biological; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D025341:Principal Component Analysis; D012016:Reference Values; D012559:Schizophrenia / Q000000981:diagnostic imaging; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D014057:Tomography, X-Ray Computed