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A critical review of the effects of de-noising algorithms on MRI brain tumor segmentation.

, , , and . EMBC, page 3934-3937. IEEE, (2011)

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An automatic brain tumor segmentation tool., , , , , and . EMBC, page 3339-3342. IEEE, (2013)Segmenting Brain Tumors Using Pseudo-Conditional Random Fields., , , , and . MICCAI (1), volume 5241 of Lecture Notes in Computer Science, page 359-366. Springer, (2008)Tumor Invasion Margin on the Riemannian Space of Brain Fibers., , , and . MICCAI (1), volume 5762 of Lecture Notes in Computer Science, page 531-539. Springer, (2009)3D Variational Brain Tumor Segmentation using a High Dimensional Feature Set., , , , and . ICCV, page 1-8. IEEE Computer Society, (2007)Fully Automated Brain Tumor Segmentation Using Two MRI Modalities., , , , , and . ISVC (1), volume 8033 of Lecture Notes in Computer Science, page 30-39. Springer, (2013)A critical review of the effects of de-noising algorithms on MRI brain tumor segmentation., , , and . EMBC, page 3934-3937. IEEE, (2011)Segmenting brain tumors using alignment-based features., , , , and . ICMLA, IEEE Computer Society, (2005)3D variational brain tumor segmentation on a clustered feature set., , , , and . Medical Imaging: Image Processing, volume 7259 of SPIE Proceedings, page 72591N. SPIE, (2009)3D variational brain tumor segmentation using Dirichlet priors on a clustered feature set., , , and . Int. J. Comput. Assist. Radiol. Surg., 7 (4): 493-506 (2012)Quick detection of brain tumors and edemas: A bounding box method using symmetry., , , , and . Comput. Medical Imaging Graph., 36 (2): 95-107 (2012)