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Texture feature based automated seeded region growing in abdominal MRI segmentation 被引量:1
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作者 Jie Wu Skip Poehlman +1 位作者 michael d. noseworthy Markad V. Kamath 《Journal of Biomedical Science and Engineering》 2009年第1期1-8,共8页
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- va... 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. 展开更多
关键词 Image SEGMENTATION Seeded REGION GROWING TEXTURE Analysis
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