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Automatic Brain Tumor Segmentation By Deep Convolutional Networks And Graph Cuts, Zhenyi Wang

Electronic Thesis and Dissertation Repository

Brain tumor segmentation in magnetic resonance imaging (MRI) is helpful for diagnostics, growth rate prediction, tumor volume measurements and treatment planning of brain tumor. The difficulties for brain tumor segmentation are mainly due to high variation of brain tumors in size, shape, regularity, location, and their heterogeneous appearance (e.g., contrast, intensity and texture variation for different tumors). Due to recent advances in deep convolutional neural networks for semantic image segmentation, automatic brain tumor segmentation is a promising research direction.

This thesis investigates automatic brain tumor segmentation by combining deep convolutional neural network with regularization by a graph cut. We investigate …