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PhD Thesis Defense: Kendall Farnham

Dec

19

Tuesday
3:00pm - 4:00pm ET

Rm B01, MacLean ESC (Zaleski)/Online

Optional ZOOM LINK

"An FPGA-based EIT System for Deep Space Medical Imaging"

Dangers associated with high radiation and microgravity exposure in space are critical challenges inhibiting us from exploring deep space and pursuing long-duration missions, as current medical systems are unable to monitor, diagnose, or treat tissue injury within physical spacecraft constraints and communication limits. Ultrasound (US) is the current imaging system used on the International Space Station, but this technology relies on telemedical support (or onboard artificial intelligence/autonomous capabilities) for both operation and diagnosis, posing challenges for crews isolated in deep space. Electrical impedance tomography (EIT) is a non-invasive, non-ionizing technology that produces images of the electrical properties of tissues and is capable of monitoring a range of long-term physiological effects of space travel (eg, tissue injury, muscle atrophy, thoracic function, cell growth, cancer detection).

To address the limitations of US, a space-compliant multi-channel EIT acquisition system was developed, and US and EIT were coupled (US-EIT) to provide high-contrast images for improved image readability by a non-expert. An integrated US-EIT probe was developed, and phantom US-EIT imaging was performed using a benchtop EIT system and GE Vivid E95 Flexible Ultrasound System (FUS) to validate the use of EIT for enhancing US. To assess the ability to detect deep pathologies (eg, abdominal hemorrhage, kidney stones), a deep-sensing phantom imaging setup was designed to include an array of ECG electrodes (modeling an abdominal belt) distal to the US-EIT probe, which forces the current to flow throughout the US imaging domain for improved depth sensitivity. We are currently integrating the EIT acquisition software with the FUS to deliver a fully integrated US-EIT system. The multi-channel FPGA-based US-EIT system provides a low-cost, low-resource medical imaging system that can accurately discriminate tissue injury while meeting the constraints of space travel, enabling deep space crews to monitor their health with greater diagnostic accuracy for selecting the most appropriate treatment and elucidating the long-term effects of deep space exposure.

Thesis Committee

  • Ryan Halter (Chair)
  • Kofi Odame
  • Geoff Luke
  • Tong In Oh (KHU)
  • Bill Thompson (NASA)

Contact

For more information, contact Julia Abraham at julia.s.abraham@dartmouth.edu.