کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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412045 | 679608 | 2015 | 13 صفحه PDF | دانلود رایگان |
The analysis of 3D medical images becomes necessary since the 3D imaging techniques have been more and more widely applied in medical applications. This paper introduces a novel segmentation method for extracting objects of interest (OOI) in 3D ultrasound images. In the proposed method, a bilateral filtering model is first applied to a 3D ultrasound volume data set for speckle reduction. We then take advantage of graph theory to construct a 3D graph, and merge sub-graphs into larger one during the segmentation process. Therefore, the proposed method can be called a 3D graph-based segmentation algorithm. After the mergence of sub-graphs, a set of minimum spanning trees each of which corresponds to a 3D sub-region is generated. In terms of segmentation accuracy, the experiments using an ultrasound fetus phantom, a resolution phantom and human fingers demonstrate that the proposed method outperforms the 3D Snake and Fuzzy C means clustering methods, indicating improved performance for potential clinical applications.
Journal: Neurocomputing - Volume 151, Part 2, 5 March 2015, Pages 632–644