Of the intracranial boundary detection techniques investigated herein, only the active contour model based techniques managed to find the contour everywhere in the MRI volume. These methods, however, require human interaction for initialization. The automatic thresholding techniques segment the images without any interaction but are error prone. Capitalizing on both techniques, a better, fully automatic intracranial boundary detection technique is developed in this thesis.
Because of multiple claims of equivalence to homomorphic filtering in the literature, and the apparent simplicity of the filter itself, this thesis pursues an RF correction technique based on explicit homomorphic filtering.