DocumentCode
1105356
Title
Shape Registration by Optimally Coding Shapes
Author
Jiang, Yifeng ; Xie, Jun ; Tsui, Hung-Tat
Author_Institution
Dept. of Diagnostic Radiol., Yale Univ., New Haven, CT
Volume
12
Issue
5
fYear
2008
Firstpage
627
Lastpage
635
Abstract
This paper formulates shape registration as an optimal coding problem. It employs a set of landmarks to establish the correspondence between shapes, and assumes that the best correspondence can be achieved when the polygons formed by the landmarks optimally code all the shape contours, i.e., obtain their minimum description length (MDL). This is different from previous MDL-based shape registration methods, which code the landmark locations. In this paper, each contour is discretized to be a set of points to make the coding feasible, and a number of strategies are adopted to tackle the difficult optimization problem involved. The resulting algorithm, called CAP, is able to yield statistical shape model with better quality in terms of model generalization error, which is demonstrated on both synthetic and biomedical shapes.
Keywords
encoding; shape measurement; minimum description length; optimally coding shapes; shape registration; Minimum Description Length (MDL) principle; Minimum description length (MDL) principle; Point Distribution Model (PDM); Shape registration; point distribution model (PDM); shape registration; statistical shape model; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
fLanguage
English
Journal_Title
Information Technology in Biomedicine, IEEE Transactions on
Publisher
ieee
ISSN
1089-7771
Type
jour
DOI
10.1109/TITB.2008.920798
Filename
4472914
Link To Document