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This dissertation, Functional Magnetic Resonance Image Registration Using Fourier Phase and Residue Error Detection by 麥可瑩, Ho-ying, Mak, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled FUNCTIONAL MAGNETIC RESONANCE IMAGE REGISTRATION USING FOURIER PHASE AND RESIDUE ERROR DETECTION Submitted by Mak Ho Ying For the degree of Master of Philosophy at the University of Hong Kong In August 2002 Image registration strategy incorporating functional magnetic resonance imaging (fMRI) data analysis is a crucial procedure to tackle the problem of the patient-head motion, generating correct activation map for visualizing the specific human brain function in response to the activation-baseline pattern. An accurate and robust registration algorithm is demanding in clinical and research practice to reduce the number of false positives and increase the sensitivity of the activation maps. To enhance a registration algorithm employing normalized mutual information (NMI), perceived as an effective registration algorithm, a phase-only NMI was used as a similarity measure to search for the optimal rigid body transformation parameters. A phase-only NMI was obtained through the extraction of phase spectrums from the amplitude image using discrete Fourier transform. Additionally, to enhance the precision of error measurement, a new residue error detection measure based on the process of phase unwrapping was implemented in determining the accuracy of the image realignment. In our experiment, several phase-based single-slice/multiple-slice fMRI should result with smaller residue errors and an evidence of increased accuracy in activation map and functional detection. It was also indicated in our proof that phase-based NMI registration was a more accurate and robust technique than intensity-based NMI registration. Fourier phase image registration (FPIR) algorithm was particularly valuable for the sub-pixel image motion (DOI: 10.5353/th_b3016330 Subjects: Error analysis (Mathematics)Magnetic resonance imagingFourier analysis

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