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13 March 2006 Segmentation of brain volume based on 3D region growing by integrating intensity and edge for image-guided surgery
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This paper presents a segmentation method of brain tissues from MR images, invented for our image-guided neurosurgery system under development. Our goal is to segment brain tissues for creating biomechanical model. The proposed segmentation method is based on 3-D region growing and outperforms conventional approaches by stepwise usage of intensity similarities between voxels in conjunction with edge information. Since the intensity and the edge information are complementary to each other in the region-based segmentation, we use them twice by performing a coarse-to-fine extraction. First, the edge information in an appropriate neighborhood of the voxel being considered is examined to constrain the region growing. The expanded region of the first extraction result is then used as the domain for the next processing. The intensity and the edge information of the current voxel only are utilized in the final extraction. Before segmentation, the intensity parameters of the brain tissues as well as partial volume effect are estimated by using expectation-maximization (EM) algorithm in order to provide an accurate data interpretation into the extraction. We tested the proposed method on T1-weighted MR images of brain and evaluated the segmentation effectiveness comparing the results with ground truths. Also, the generated meshes from the segmented brain volume by using mesh generating software are shown in this paper.
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Baigalmaa Tsagaan, Keiichi Abe, Masahiro Goto, Seiji Yamamoto M.D., and Susumu Terakawa M.D. "Segmentation of brain volume based on 3D region growing by integrating intensity and edge for image-guided surgery", Proc. SPIE 6141, Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display, 61412D (13 March 2006);

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