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Statistical list-mode image reconstruction and motion compensation techniques in high-resolution positron emission tomography (PET) Rahmim, Arman
Abstract
The work presented here is devoted to the proposal and investigation of 3D image reconstruction algorithms suitable for high resolution positron emission tomography (PET). In particular, we have studied imaging techniques applicable to the high resolution research tomograph (HRRT): a 3Donly state-of-the-art dedicated brain tomograph. The HRRT poses a number of unique challenges, most significant of which include presence of gaps in-between the detector heads, as well as the very large number of lines-ofresponse (LORs) which it is able to measure (~4.5x10⁹), exceeding most modern PET scanners by 2-3 orders of magnitude. To address the existing issues, we have developed and implemented statistical list-mode image reconstruction as a powerful technique applicable to the high resolution data obtained by the HRRT. We have furthermore verified applicability of this technique to dynamic (4D) PET imaging, thus qualifying the technique as viable and accurate for the research intended to be performed on the scanner. We have paid particular attention to the study of convergent algorithms; i.e. iterative algorithms which (with further iterations) consistently improve such figures of merit as resolution and contrast, relevant to research and clinical tasks. With the spatial resolution in modern high resolution tomographs (including the HRRT) reaching the 2-3mm FWHM range, small patient movements during PET imaging can become a significant source of resolution degradation. We have thus devoted a portion of this dissertation to the proposal of new, accurate and practical motion-compensation techniques, and studied them on the HRRT. We have theoretically proposed and experimentally validated the benefits of modeling the motion into the reconstruction task, thus signaling the way beyond the existing purely event-driven motioncompensation techniques.
Item Metadata
Title |
Statistical list-mode image reconstruction and motion compensation techniques in high-resolution positron emission tomography (PET)
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2005
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Description |
The work presented here is devoted to the proposal and investigation of
3D image reconstruction algorithms suitable for high resolution positron
emission tomography (PET). In particular, we have studied imaging techniques
applicable to the high resolution research tomograph (HRRT): a 3Donly
state-of-the-art dedicated brain tomograph. The HRRT poses a number
of unique challenges, most significant of which include presence of gaps
in-between the detector heads, as well as the very large number of lines-ofresponse
(LORs) which it is able to measure (~4.5x10⁹), exceeding most
modern PET scanners by 2-3 orders of magnitude.
To address the existing issues, we have developed and implemented statistical
list-mode image reconstruction as a powerful technique applicable to the
high resolution data obtained by the HRRT. We have furthermore verified
applicability of this technique to dynamic (4D) PET imaging, thus qualifying
the technique as viable and accurate for the research intended to be
performed on the scanner. We have paid particular attention to the study
of convergent algorithms; i.e. iterative algorithms which (with further iterations)
consistently improve such figures of merit as resolution and contrast,
relevant to research and clinical tasks.
With the spatial resolution in modern high resolution tomographs (including
the HRRT) reaching the 2-3mm FWHM range, small patient movements
during PET imaging can become a significant source of resolution
degradation. We have thus devoted a portion of this dissertation to the proposal
of new, accurate and practical motion-compensation techniques, and
studied them on the HRRT. We have theoretically proposed and experimentally
validated the benefits of modeling the motion into the reconstruction
task, thus signaling the way beyond the existing purely event-driven motioncompensation
techniques.
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Extent |
video/mp4
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Genre | |
Type | |
Language |
eng
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Date Available |
2009-12-22
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0092303
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2005-05
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
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Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.