A Novel Medical Image Segmentation Method using Dynamic Programming

Author

Yan Zhang ; Matuszewski, Bogdan J. ; Lik-Kwan Shark ; Moore, C.J.

Author_Institution

Univ. of Central Lancashire, Preston

fYear

2007

fDate

4-6 July 2007

Firstpage

69

Lastpage

74

Abstract

A novel method is proposed to segment objects in medical images whose boundaries can be described as closed curves. Based on an image with the enhanced boundary of an object of interest, the segmentation method consists of three key steps, namely, the polar transformation, dynamic programming and curve fitting. A 3D object in volumetric data can be segmented on a slice-by-slice basis by only specifying one point inside the 3D object of interest as the pole for the polar transformation. The method is also shown to be able to segment objects with very weak boundaries.

Keywords

curve fitting; dynamic programming; image segmentation; medical image processing; 3D object; curve fitting; dynamic programming; medical image segmentation method; polar transformation; volumetric data; Active contours; Biomedical imaging; Curve fitting; Dynamic programming; Image segmentation; Law; Legal factors; Pixel; Signal processing; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Medical Information Visualisation - BioMedical Visualisation, 2007. MediVis 2007. International Conference on

Conference_Location

Zurich

Print_ISBN

0-7695-2904-6

Type

conf

DOI

10.1109/MEDIVIS.2007.2

Filename

4272113