Abstract
Abstract Cancer is a dense and an abnormal rapid multiplication (proliferation) of cells in the tissues of the human body. The brain tumor is one of the most dangerous and deadly tumors. Fortunately, the evolution of science has allowed us to create very efficient medical imaging techniques in order to discover this type of cancer. Chief among these techniques is magnetic resonance imaging (MRI) which is a very efficient technique compared to ultrasound. In this work, we are interested in the detection of this type of cancer allowing a three-dimensional (3D) reconstruction of MRI images. The segmentation methods used are based primarily on the Fuzzy C-Means algorithm that classifies and isolates parts of the brain tissue, and secondly on Distance Regularized Level Set Evolution technique for tumor detection. The obtained results show the effectiveness of this approach to detect brain tumor. The 3D reconstruction is finally carried out to better visualize the tumor as a whole and to detect its expansion. It is conducted using an indirect volume rendering method, which is the Marching Cubes algorithm.
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