The registration of volumetric data from sources as MR, CT or PET, is of importance for surgical planning, diagnosis, clinical track of events, evaluation of radiotherapeutical procedures and medical research. Alignment can be achieved in many ways, one of which is by maximizing a measure of similarity between images, such as the mutual information similarity. This technique requires no a priori model of the relationship between modalities, it only assumes that one volume provides the most information about the other one when they are correctly registered.
This project presents a wide overview of existing medical image registration methods. Registration methods are classified according to the different aspects of mutual-information based registration. Three state-of-the-art registration software packages, available for public use, are explored. The software was compared in terms of registration accuracy (using consistency measurements), visual inspections, and by applying, for the first time, clinical tests on Multiple Sclerosis (MS) patients.
Our thanks to Dr. Anat Achiron, Multiple Sclerosis center, Sheba Medical center, Tel-Hashomer, Israel.
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