Adaptation of microwave-induced thermoacoustic imaging to subcutaneous vasculature : toward an all-electronic, embeddable imaging platform for biometric applications
Abstract/Contents
- Abstract
- Imaging of subcutaneous vasculature is of great interest for biometric security and point-of-care medicine. In this thesis, I investigated the feasibility of microwave-induced thermoacoustic tomography as a safe, compact, low-power, and cost-effective imaging technique for subcutaneous vasculature by means of application-specific customization. I began with a focus on order-of-magnitude improvements in the required microwave-domain excitation power and ultimately demonstrated the first miniturizable adaptation of thermoacoustic (TA) imaging specifically designed to detect shallow penetration-depth, subcutaneous vasculature. The key contribution was introducing a new concept and design methodology of near-field RF applicators, which resulted in proof-of-concept TA imaging of synthetic phantoms, plant vasculature, and earthworm blood vessels with only 50 W of peak power, or 42 mW average power, at 300 um resolution. The proposed RF applicator design enabled uniform, orientation-independent illumination of vasculature phantoms with only 10% variation. I continued with customization in the ultrasound-domain, where I introduced a new concept of spatial difference imaging (SDI) implemented on silicon as an 8-channel TA analog front-end (AFE) designed on Texas Instrument Inc.'s proprietary 180 um BCD process. The AFE simultaneously achieves less than 0.75 pA/rHz effective current noise and less than 0.64 nV/rHz effective voltage noise over a target bandwidth of 15 MHz when loaded with up to 10 pF of sensor capacitance. Additionally, the AFE is capable of maintaining an input CMRR greater than 60 dB with a minimum SFDR of 50 dBc that achieves the desired output linearity over the target bandwidth while handling up to 50 pF loading per channel, which is critical for SDI-based TA imaging in the intended application known to require at least 40 dB of imaging dynamic range. This new SDI concept not only required an application-specific circuit design approach in hardware, but innovations in post-processing for image-reconstruction on the software side as well. In particular, I established a theoretical framework to formalize an understanding of SDI, which resulted in an image-reconstruction algorithm that elegantly splits into a one-time, computation-heavy algorithm intended for a traditional computer or server and a light computation that can run on a mobile device or microprocessor during scan-time. Proof-of-concept measurements show that SDI alleviates dynamic-range (DR) requirements by 22 dB, boosting vascular signatures by +40% to +80% while rejecting skin signatures by -20%, and addresses the remaining challenge of low-SNR TA imaging. I further demonstrate that, with a fully SDI-customized AFE, high quality imaging is possible with only 40 dB of DR, without the need of any time-gain control, all with greatly reduced digitization complexity of only 8-bits. Finally, all the proposed customization leading to a miniature, high-resolution, high-contrast, low-power yet highly-sensitive TA imager will inevitably have to also deal with the reality of interference in a practical manner. To address this, I outline interference mitigation strategies, such as multi-physics-optimized construction material selection and active microwave-to-ultrasound leakage cancellation techniques, needed to transform my proof-of-concept prototypes into a more user-friendly final product.
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 | 2021; ©2021 |
| Publication date | 2021; 2021 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Seyed Aliroteh, Seyed Miaad |
|---|---|
| Degree supervisor | Arbabian, Amin |
| Thesis advisor | Arbabian, Amin |
| Thesis advisor | Khuri-Yakub, Butrus T, 1948- |
| Thesis advisor | Lee, Thomas H, 1959- |
| Degree committee member | Khuri-Yakub, Butrus T, 1948- |
| Degree committee member | Lee, Thomas H, 1959- |
| Associated with | Stanford University, Department of Electrical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Miaad Seyed Aliroteh. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2021. |
| Location | https://purl.stanford.edu/dh344ms5016 |
Access conditions
- Copyright
- © 2021 by Seyed Miaad Seyed Aliroteh
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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