Microwave tomography for clinical head imaging

#IEEE #microwaves #tomography #imaging
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Microwave tomography faces several challenges in its transition toward clinical application. This seminar introduces the approaches to address these challenges. Our investigation concluded that reasonable clinical images can be generated when using a calibrated multi-frequency microwave tomography algorithm, supported by a proper frequency selection.

The calibration aims at matching the forward and inverse solvers, whereas frequency selection aligns measurement with simulation. 

In this seminar, we compare the imaging results with the ground truths (MRI and CT), clarifying the potential and challenges of clinical microwave tomography.


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  • IN-PERSON: The University of Queensland
  • Brisbane, Queensland
  • Australia 4072
  • Building: 49 (Advanced Engineering building)
  • Room Number: 653
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  • Starts 03 August 2025 01:00 PM UTC
  • Ends 08 August 2025 12:00 AM UTC
  • No Admission Charge

  Speakers

Dr. Lei Guo

Topic:

Microwave tomography for clinical head imaging

Biography:

Lei Guo received the B.Sc. degree in Electronics Information Science and Technology from Xidian University, Xi’an, China, in 2010, and the M.Eng. degree in Microwave Engineering and the Ph.D. degree in Electrical Engineering from the School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, QLD, Australia, in 2012 and 2017, respectively. He is currently a Senior Lecturer in the School of Electrical Engineering and Computer Science at The University of Queensland.

His research interests include electromagnetic medical imaging (microwave and MRI), physics-guided deep learning for electromagnetic imaging, biomedical signal processing, and microwave circuit design for millimetre-wave antenna array systems.

Dr. Guo received the IEEE R.W.P. King Award for the best paper published in IEEE Transactions on Antennas and Propagation in 2015. He was awarded an Advance Queensland Fellowship in 2021 and is the recipient of two Australian Research Council (ARC) Discovery Project Grants in 2023 and 2024.

Address:The University of Queensland, , Queensland, Australia