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Abstract #1376

Semi-automatic segmentation of medulloblastoma using active contour method

Ka Hei Lok1, Lin Shi2,3, Queenie Chan4, and Defeng Wang5,6

1Department of Imaging and Intenvntional Radiology, The Chinese University of Hong Kong, Sha Tin, Hong Kong, 2Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Sha Tin, Hong Kong, 3Chow Yuk Ho Technology Centre for Innovative Medicine, The Chinese University of Hong Kong, Sha Tin, Hong Kong, 4Philips Healthcare, Hong Kong, Hong Kong, 5Research Center for Medical Image Computing, Department of Imaging and Intenvntional Radiology, The Chinese University of Hong Kong, Sha Tin, Hong Kong, 6Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China, People's Republic of

Brain tumours are the second commonest form of childhood malignancy while medulloblastoma is the most common brain tumor in children. Accurate Segmentation of medulloblastoma is necessary for maximum tumor surgical removal. We proposed a novel method to segment medulloblastoma by modifying signed pressure function (SPF) function in Gaussians Filtering Regularized Level Set (SBGRLS) method. Quantitative validation is performed in this project. The method is proved to be clinical-oriented which is fast, robust, accurate with minimal user interaction.

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