Review on MRI-Based Brain Segmentation Methods
Magnetic Resonance Imaging (MRI) is one of the power full visualization techniques, which is mainly used for the treatment of cancer. Magnetic Resonance Imaging is a radiation-based technique which represents the internal structure of the body in terms of intensity variation of radiated wave generated by the biological system when it is exposed to radio frequency pulses. MRI is mostly adopted by the radiologist for visualization of internal structure of the human body without any surgery. Accurate segmentation of MRI image is essential for the diagnosis of brain tumor by computer aided clinical tool. Brain tumor detection and segmentation is one of the most challenging and time-consuming task in the domain of medical image processing. After appropriate segmentation of brain MRI images, tumor is classified to be either malignant or benign, which is a complicated task since complexity varies in proportion to the tumor tissue traits like its shape, size, gray level intensities and location. This paper provides a review of segmentation algorithms specifically on brain tumor MR Images.
Keywords - Image Processing, Image Segmentation, Brain tumor, MRI (Magnetic Resonance Image)