Level set estimation on the sphere

Author

Lorbert, Alexander ; Ramadge, Peter J.

Author_Institution

Dept. of Electr. Eng., Princeton Univ., Princeton, NJ, USA

fYear

2010

fDate

14-19 March 2010

Firstpage

2202

Lastpage

2205

Abstract

We investigate a technique for estimating level sets of functionals on the 2-sphere. The surface of the sphere is finely partitioned using a tree decomposition and a candidate level set is obtained by minimizing a regularized cost on the tree. A cycle spinning scheme, implemented as an ensemble classification method, is developed to decrease the variance of the tree-based estimate. Both constructions are compatible with many existing hierarchical discretizations of the 2-sphere, e.g. HEALPix and HTM. We present simulation results of a synthetic data set and an fMRI data set.

Keywords

biomedical MRI; image classification; matrix decomposition; medical image processing; HEALPix; HTM; cycle spinning scheme; ensemble classification method; fMRI data set; hierarchical discretizations; level set estimation; sphere; tree decomposition; tree-based estimate variance; Classification tree analysis; Costs; Data analysis; Data mining; Image edge detection; Level set; Mesh generation; Pattern classification; Spinning; Statistics; Image edge analysis; Mesh generation; Pattern classification; Quadtrees;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on

Conference_Location

Dallas, TX

ISSN

1520-6149

Print_ISBN

978-1-4244-4295-9

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2010.5495725

Filename

5495725