Dynamic edge tracing for 2D image segmentation

Author

Withey, D.J. ; Koles, Z.J. ; Pedrycz, W.

Author_Institution

Dept. of Biomed. Eng., Alberta Univ., Edmonton, Alta., Canada

Volume

3

fYear

2001

fDate

2001

Firstpage

2657

Abstract

A novel segmentation technique which may be useful for two dimensional (2D) magnetic resonance (MR) image segmentation is presented. The technique utilizes a dynamic target tracking algorithm and a Kalman filter and permits edges to be followed in the presence of intensity variation similar to that found in MR images. Segmentation of two synthetic test images, one with intensity nonuniformity and one without, is performed. Fuzzy c-means clustering with pixel intensity features is used to segment the same test images for qualitative comparison.

Keywords

Kalman filters; biomedical MRI; edge detection; image segmentation; medical image processing; 2D image segmentation; dynamic edge tracing; fuzzy c-means clustering; intensity nonuniformity; intensity variation; magnetic resonance imaging; medical diagnostic imaging; pixel intensity features; synthetic test images; Biomedical engineering; Clustering algorithms; Heuristic algorithms; Image segmentation; Labeling; Magnetic resonance; Pixel; Radio frequency; Target tracking; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE

ISSN

1094-687X

Print_ISBN

0-7803-7211-5

Type

conf

DOI

10.1109/IEMBS.2001.1017329

Filename

1017329