title: A Framework for Joint Image-and-Shape Analysis.
abstract: Techniques in medical image analysis are many times used for the comparison or regression on the intensities of images. In general, the domain of the image is a given Cartesian grids. Shape analysis, on the other hand, studies the similarities and differences among spatial objects of arbitrary geometry and topology. Usually, there is no function defined on the domain of shapes. Recently, there has been a growing needs for defining and analyzing functions defined on the shape space, and a coupled analysis on both the shapes and the functions defined on them. Following this direction, in this work we present a coupled analysis for both images and shapes. As a result, the statistically significant discrepancies in both the image intensities as well as on the underlying shapes are detected. The method is applied on both brain images for the schizophrenia and heart images for atrial fibrillation patients.
authors.affiliation: Department of Electrical and Computer Engineering and the Comprehensive Cancer Center, the University of Alabama at Birmingham; 1150 10th Avenue South, Birmingham, AL 35294.
authors.forename: Yi
authors.initials: Y
authors.lastname: Gao
authors.affiliation: Departments of Computer Science and Applied Mathematics/Statistics, Stony Brook University, Stony Brook, New York, 11794.
authors.forename: Allen
authors.initials: A
authors.lastname: Tannenbaum
authors.affiliation: Department of Psychiatry, Harvard Medical School, 1249 Boylston St, Boston, MA, 02215.
authors.forename: Sylvain
authors.initials: S
authors.lastname: Bouix