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Texture feature based automated seeded region growing in abdominal MRI segmentation
Department of Computing and Software
Department of Computing and Software
Brain-Body Institute, St. Joseph’s Healthcare, Hamilton, Ontario, Canada
D epartment of Medicine, McMaster University, Hamilton, Ontario, Canada
- 1 Department of Computing and Software
- 2 Department of Computing and Software
- 3 Brain-Body Institute, St. Joseph’s Healthcare, Hamilton, Ontario, Canada
- 4 D epartment of Medicine, McMaster University, Hamilton, Ontario, Canada
Journal of Biomedical Science and Engineering·Volume 02 (2009)·Pages 1–8·Published 10 February 2009·DOI10.4236/jbise.2009.21001
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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.
KeywordsImage SegmentationSeeded Region GrowingTexture Analysis
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