DocumentCode :
1937874
Title :
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
Link To Document :
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