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GEOMETRIC METHODS FOR IMAGE REGISTRATION AND ANALYSIS
by
Anand Arvind Joshi
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ELECTRICAL ENGINEERING)
August 2008
Copyright 2008 Anand Arvind Joshi
Object Description
| Title | Geometric methods of image registration and analysis |
| Author | Joshi, Anand Arvind |
| Author email | ajoshi@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Electrical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-06-08 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-07-29 |
| Advisor (committee chair) | Leahy, Richard M. |
| Advisor (committee member) |
Nayak, Krishna Bonahon, Francis |
| Abstract | Registration and analysis of neuro-imaging data presents a challenging problem due to the complex folding patterns in the human brain. Specifically, the cortical surface of the human brain can be modeled as a highly convoluted 2D surface. Since it is non-flat, the non-Euclidean geometry of the cortex needs to be accounted for while performing registration and subsequent signal processing of anatomical and functional signals on the cortex. Techniques from differential geometry offer a powerful set of tools to deal with the convoluted nature of the cortex. We present a method based on p-harmonic mapping for performing cortical surface parameterization. A 2D coordinate system induced by the flat mapping is then used to compute the surface metric and discretize derivatives in the surface geometry. For performing inter-subject cortical registration based on sulcal landmarks, we generalize thin-plate splines to non-flat surfaces by using covariant derivatives. We also present an FEM based method for simultaneous parameterization and registration of sulcal landmarks based on elastic energy minimization. The manual effort required for selecting the sulcal landmarks can be minimized if we choose an optimal set of such landmarks. We present a method for optimally selecting a subset of any size from a set of candidate sulcal landmarks and also predict the associated registration error for that subset using conditional distributions. Surface signals from individual brains can be brought to a common atlas surface by using these surface based registration techniques.; Isotropic and anisotropic diffusion filtering methods are formulated for processing of the cortical data. This is performed by using parameterization-based methods which use covariant diffusion operators in the flat space. When the surface data is a point-set on the cortex, we propose a method to quantify its mean and variance with respect to the surface geometry.; The registration techniques presented for surface alignment are extended to volumes to perform full surface and volume registration. This is done by using volumetric harmonic mappings that extend the surface point correspondence to the cortical brain volume. Finally, the volumetric registration is refined by using inverse-consistent linear elastic intensity registration. This set of methods presents a unified framework for registration and analysis of brain signals for inter-subject neuroanatomical studies. |
| Keyword | brain image registration; harmonic maps; PDE based |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m1444 |
| Rights | Joshi, Anand Arvind |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Joshi-20080729 |
| Archival file | uscthesesreloadpub_Volume23/etd-Joshi-20080729.pdf |
Description
| Title | Page 1 |
| Full text | GEOMETRIC METHODS FOR IMAGE REGISTRATION AND ANALYSIS by Anand Arvind Joshi A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (ELECTRICAL ENGINEERING) August 2008 Copyright 2008 Anand Arvind Joshi |
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