Texture Feature based Automated Seeded Region Growing in Abdominal MRI Segmentation

Author

Wu, Jie ; Poehlman, Skip ; Noseworthy, Michael D. ; Kamath, Markad V.

Author_Institution

Dept. of Comput. & Software, McMaster Univ., Hamilton, ON

Volume

2

fYear

2008

fDate

27-30 May 2008

Firstpage

263

Lastpage

267

Abstract

A new texture feature based seeded region growing algorithm is proposed for the automated segmentation of organs in Abdominal MR image. Co-occurrence texture feature and semi-variogram texture feature are extracted from the image and the seeded region growing algorithm is run on these feature spaces. With a given Region of Interest(ROI), a seed point is automatically picked up based on three homogeneity criteria. A threshold is then obtained by taking a lower value just before the one causing ´explosion´. This algorithm is tested on 12 series of 3D abdominal MR images.

Keywords

biomedical MRI; feature extraction; image segmentation; image texture; medical image processing; abdominal MRI; automated seeded region growing; cooccurrence texture feature; feature extraction; image segmentation; semivariogram texture feature; Abdomen; Biomedical computing; Biomedical engineering; Biomedical imaging; Feature extraction; Image analysis; Image segmentation; Image texture analysis; Magnetic resonance imaging; Medical diagnostic imaging; Seeded Region Growing; Texture Feature;

fLanguage

English

Publisher

ieee

Conference_Titel

BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on

Conference_Location

Sanya

Print_ISBN

978-0-7695-3118-2

Type

conf

DOI

10.1109/BMEI.2008.352

Filename

4549175