Segmentation of brain images has been a prominent area of research in the field of medical imaging in the recent past. This work concentrates on segmentation of brain images acquired using Magnetic Resonance Imaging (MRI) technique. Brain image consists of many different parts that are of interest to practitioners. Automatic segmentation of all these parts has been a challenging task. In this paper a system for localizing the region of interest and automated segmentation of brain parts by using histogram of oriented gradients and SVM Classifier has been presented. The system is trained using specific parts of the brain image separately. Once properly trained, the system can segment the part with which it has been trained from the test dataset. Here, for discussion the region of interest around ventricles in axial view and corpus callosum in sagittal view has been considered.
N. Madhesh and Dr. Hema Menon P., “Automated segmentation of brain parts from MRI image slices”, International Journal of Pure and Applied Mathematics, vol. 114, no. 11 Special Issue, pp. 36-46, 2017.