Low power techniques for wireless MRI receiver arrays
Abstract/Contents
- Abstract
- A longtime goal of the MRI community has been the development of conformal wireless receiver arrays as an alternative to their bulky, rigid, and often uncomfortable standard implementations. Current MR receive channels require high power consumption to enable the stringent Noise Figure, Gain, and Dynamic Range necessary for clinically relevant data. Combined with high channel counts (32 to 96), power consumption is a major challenge when translating to the wireless use case. As the pre-amplifier is the receiver element that determines many performance metrics and can consume over 200mW it is a prime candidate for re-evaluation. In this work, I will present an alternative SiGe HBT based MRI pre-amplifier with power con- sumption up to 28x less than current HEMT-based devices. Its potential for integration is first evaluated through behavioral modeling alongside a real image dataset. Following initial simulated results, its impact on imaging performance is evaluated via benchtop evaluation with MR-relevant receiver components. Alongside this pre-amplifier I propose a semi-blind calibration and compensa- tion framework that can be integrated into the existing pre-scan period for dynamic range expansion, as this amplifier features reduced linearity relative to MR standards. The application of this cali- bration method is able to reduce errors stemming from non-linear distortion to levels comparable to industry reference amplifiers. This is followed by preliminary work integrating this amplifier and calibration method into a 1.5T system demonstrating example calibration experiments and phantom images. The presented calibration method is applied to these images recovering image quality and illustrating the potential for the utility of the presented amplifier and calibration method. This concludes in a discussion regarding system level integration considerations for such a method in high-channel count arrays.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Vassos, Christopher William |
|---|---|
| Degree supervisor | Pauly, John (John M.) |
| Thesis advisor | Pauly, John (John M.) |
| Thesis advisor | Rivas-Davila, Juan |
| Thesis advisor | Scott, Greig Cameron, 1962- |
| Degree committee member | Rivas-Davila, Juan |
| Degree committee member | Scott, Greig Cameron, 1962- |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Christopher Vassos. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/zx361zj0109 |
Access conditions
- Copyright
- © 2022 by Christopher William Vassos
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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