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18 September 2018 Representing phase over irregular closed surfaces (Conference Presentation)
Philip J. Bones
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Proceedings Volume 10772, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2018; 107720N (2018) https://doi.org/10.1117/12.2320711
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States
Abstract
After the implantation of metal prostheses, such as hip and knee replacements, there is a need to monitor the success of the implantation and, in some cases, to determine the cause of continuing pain. MRI would be well suited to visualizing the possible changes in soft tissue surrounding the implant, however its success is badly affected by artifacts due to the presence of the metal in the scanner's strong magnetic field. The Dixon method allows the variation in the magnetic field to be estimated, but only as the wrapped phase of a complex quantity. High field gradients near the metal mean that the phase estimate is highly undersampled and challenging to unwrap. In 2017, we reported a new algorithm named POP (phase estimation by onion peeling) and conjectured that our initial implementation for 2-D imaging could be extended to 3-D imaging. This would require expanding the phase estimate using a suitable smoothly varying basis over closed enveloping surfaces which are irregular. The algorithm initially estimates the phase over a surface which surrounds the implant and is sufficiently distant from the implant that the phase is well sampled. Then, surface-by-surface, the smooth nature of the true phase is invoked to form an initial estimate of the true phase on the next surface. That estimate is corrected using the sampled wrapped phase data arising from the MR scan. In this paper, I investigate the choice of basis functions and methods for projecting them onto irregular surfaces which are typical for applying POP to imaging the soft tissue surrounding hip implants.
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Philip J. Bones "Representing phase over irregular closed surfaces (Conference Presentation)", Proc. SPIE 10772, Unconventional and Indirect Imaging, Image Reconstruction, and Wavefront Sensing 2018, 107720N (18 September 2018); https://doi.org/10.1117/12.2320711
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KEYWORDS
Metals
Natural surfaces
Magnetism
Statistical analysis
Tissues
Magnetic resonance imaging
Stereoscopy
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