TITLE:
Texture feature based automated seeded region growing in abdominal MRI segmentation
AUTHORS:
Jie Wu, Skip Poehlman, Michael D. Noseworthy, Markad V. Kamath
KEYWORDS:
Image Segmentation, Seeded Region Growing, Texture Analysis
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.2 No.1,
February
13,
2009
ABSTRACT: A new texture feature-based seeded region growing algorithm is proposed for automated segmentation of organs in abdominal MR images. 2D Co-occurrence texture feature, Gabor texture feature, and both 2D and 3D Semi- variogram texture features are extracted from the image and a seeded region growing algorithm is run on these feature spaces. With a given Region of Interest (ROI), a seed point is automatically se-lected 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 ab-dominal MR images.