Image reconstruction for high-resolution PET : GPU-accelerated strategies for improving image quality and accuracy
Abstract/Contents
- Abstract
- Molecular imaging can interrogate subtle molecular disease signatures non-invasively in living subjects. Positron emission tomography (PET), one particular molecular imaging modality, is able to sense molecular signals deep within tissue. Although PET is well suited for imaging signals associated with cancerous lesions in humans, it is still unable to resolve very small (< 2 mm) structures. Improving the spatial resolution of PET is an active area of research driven by many potential applications. However, the new generation of high-resolution PET systems raise new challenges for image reconstruction. In this dissertation, several strategies and algorithms are proposed to enable accurate and practical image reconstruction for high-resolution PET. Reconstruction is performed directly from the list-mode data via maximum-likelihood estimation. A shift-varying model of the imaging process is incorporated in the reconstruction. For fast reconstruction, the calculations are implemented using highly-parallel graphics processing units (GPU). A Bayesian sequence reconstruction algorithm is also used to position the annihilation photons that deposit energy in multiple detection elements. We show that the reconstruction provides near-uniform spatial resolution throughout the field-of-view, enhanced trade-off between noise and contrast, and better image quantitative accuracy. Furthermore, thanks to the computing power of graphics hardware, reconstruction times are practical for clinical applications.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Copyright date | 2010 |
| Publication date | 2009, c2010; 2009 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Pratx, Guillem |
|---|---|
| Associated with | Stanford University, Department of Electrical Engineering |
| Primary advisor | Levin, Craig |
| Thesis advisor | Levin, Craig |
| Thesis advisor | Hanrahan, P. M. (Patrick Matthew) |
| Thesis advisor | Pauly, John (John M.) |
| Advisor | Hanrahan, P. M. (Patrick Matthew) |
| Advisor | Pauly, John (John M.) |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Guillem Pratx. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2010. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2010 by Guillem Pratx
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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