Title :
Signed poisson map for shape analysis
Author :
Gao, A. Yi ; Bouix, B. Sylvain
Author_Institution :
Dept. of ECE & CCC, Univ. of Alabama at Birmingham, Birmingham, AL, USA
fDate :
April 29 2014-May 2 2014
Abstract :
Statistical shape analysis is a widely studied topic with applications ranging in biology, anatomy, neuroscience, agriculture, paleontology, etc. In many cases, two sets of shapes are input to the algorithm and the output is a mean shape with a scalar map defined on it indicating the local discrepancy between the two groups. In this work, we propose a new shape analysis algorithm. It is able to handle shapes with arbitrary topology. Specifically, the algorithm constructs a Signed Poisson Map (SPM) by solving two Poisson equations on the volumetric shapes, and statistical analysis is then carried out on the SPMs. The algorithm is tested on both synthetic and real shape data sets.
Keywords :
Poisson equation; biomechanics; brain; deformation; medical image processing; statistical analysis; Poisson equations; SPM; agriculture; anatomy; arbitrary topology; biology; deformation; neuroscience; paleontology; real shape datasets; scalar map; signed Poisson map; statistical shape analysis; striatum; synthetic shape datasets; volumetric shapes; Algorithm design and analysis; Biology; Biomedical imaging; Educational institutions; Niobium; Poisson equations; Shape; Poisson equation; Shape analysis;
Conference_Titel :
Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on
Conference_Location :
Beijing
DOI :
10.1109/ISBI.2014.6867890