This remainder of this thesis is subdivided into the following chapters:
Chapter 2, Magnetic Resonance Imaging and Data Characteristics, provides a brief overview of the principles of MRI and describes MRI data characteristics important to the problems studied in this thesis.
Chapter 3, Previous Work, reviews the contributions of other researchers in the areas of intracranial boundary detection and RF correction.
Chapter 4, Nonlinear Anisotropic Diffusion Filtering, describes the named filter in detail. The filter is used to isolate the brain in the intracranial boundary detection scheme presented herein.
Chapter 5, Active Contour Models, describes the active contour model algorithm used to find the edge of the brain in the final step of the new intracranial boundary detection scheme.
Chapter 6, Homomorphic Filtering, introduces homomorphic filtering which is used by the RF correction algorithm developed in this thesis.
Chapter 7, Intracranial Boundary Detection and RF Correction, details the new automatic intracranial boundary detection and RF correction technique.
Chapter 8, Results, presents the results of testing the scheme from Chapter 7 on several MRI data sets. The new intracranial boundary detection and RF correction technique is evaluated based entirely on these observed qualitative results; it is not evaluated on the basis of the ``success'' of MS lesion segmentation, registration, nor image compression.
Chapter 9, Summary, concludes the thesis by summarizing the new intracranial boundary detection and RF correction scheme and suggests future work in relation to observed results.