Microwave Radar Systems for Medical Imaging and Sensing Applications

Ultra-wide band microwave imaging is a promising method for the detection of several diseases inside a human body including cancer and stroke. The advantages of microwave imaging over conventional methods such as computed tomography (CT) scan, mammography and X-ray are low cost and a non-ionisation method. There are two main categories of microwave imaging: Microwave tomography and Ultra-wideband (UWB) radar based imaging. Microwave tomography works by reconstructing the dielectric constant of the imaging object, based on the scattered EM field of a single frequency or multiple frequencies. The UWB method transmits a short pulse towards a target and its scattered field is measured. UWB microwave imaging offers fast detection due to less computational power required compared to tomography technique.

Several research studies are being conducted within this group for medical microwave imaging. These include: investigation of microwave sensing for diagnosing brain diseases such as Alzheimer's disease, stroke, etc., development of a wearable device for microwave head imaging for detecting stroke and neurodegenerative diseases, wearable and portable system for lung and breast cancer detections, and microelectromechanical system (MEMS) based phase shifter for future integration with antenna array for beam steering application. 

Present projects address the following areas:

  • Investigation of electromagnetic wave interaction with human body
  • Development of wearable devices for microwave medical imaging and diagnostics
  • Miniaturisation of antenna for medical and wireless applications
  • Tissue characterisation and dielectric measurements of healthy and diseases tissues
  • Fabrication of realistic artificial phantoms, such as head, breast and lung, for microwave imaging testing
  • Development of microave imaging algorithms for noninvasive medical imaging
  • Implementation of Big Data approaches for scaling and processing of RF data
  • Implementation of AI and machine learning algorithms to classify and predict the onset of diseases.
  • MEMS varactor for tunable RF front end components for future wireless communication
  • MEMS DMTL phase shifter for low frequency applications

Details of the projects can be found below:

Recent Publications:

  • I. Saied, T. Arslan, R. Ullah, C. Liu and F. Wang, "Hardware Accelerator for Wearable and Portable Radar-based Microwave Breast Imaging Systems," 2021 IEEE International Symposium on Circuits and Systems (ISCAS), 2021, pp. 1-5, doi: 10.1109/ISCAS51556.2021.9401407.
  • Ullah, R.; Arslan, T. Parallel Delay Multiply and Sum Algorithm for Microwave Medical Imaging Using Spark Big Data Framework. Algorithms 2021, 14, 157. https://doi.org/10.3390/a14050157
  • R. Ullah and T. Arslan, "Detecting Pathological Changes in the Brain Due to Alzheimer Disease Using Numerical Microwave Signal Analysis," 2020 IEEE International RF and Microwave Conference (RFM), 2020, pp. 1-4, doi: 10.1109/RFM50841.2020.9344758.
  • Ullah, R.; Arslan, T. PySpark-Based Optimization of Microwave Image Reconstruction Algorithm for Head Imaging Big Data on High-Performance Computing and Google Cloud Platform. Appl. Sci. 2020, 10, 3382. https://doi.org/10.3390/app10103382
  • I. Saied, T. Arslan, S. Chandran, C. Smith, T. Spires-Jones and S. Pal, "Non-Invasive RF Technique for Detecting Different Stages of Alzheimer’s Disease and Imaging Beta-Amyloid Plaques and Tau Tangles in the Brain," in IEEE Transactions on Medical Imaging, vol. 39, no. 12, pp. 4060-4070, Dec. 2020, doi: 10.1109/TMI.2020.3011359.
  • I. Saied, S. Chandran and T. Arslan, "Integrated Flexible Hybrid Silicone-Textile Dual-Resonant Sensors and Switching Circuit for Wearable Neurodegeneration Monitoring Systems," in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 6, pp. 1304-1312, Dec. 2019.
  • I. Saied and T. Arslan, "Non-Invasive Wearable RF Device towards Monitoring Brain Atrophy and Lateral Ventricle Enlargement," in IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology.
  • I. Saied, M. S. R. Bashri, T. Arslan, C. Smith and S. Chandran, "Dielectric Measurements of Brain Tissues with Alzheimer’s Disease Pathology in the Microwave Region," 2019 IEEE International Symposium on Medical Measurements and Applications (MeMeA), Istanbul, Turkey, 2019, pp. 1-6.
  • I. Saied and T. Arslan, "Microwave Imaging Algorithm for Detecting Brain Disorders," 2019 29th International Conference Radioelektronika (RADIOELEKTRONIKA), Pardubice, Czech Republic, 2019, pp. 1-5.
  • I. Saied, M. S. R. Bashri, and T. Arslan, “Wideband Textile-Based Sensors for Detecting Brain Disorders,” Antennas & Propagation Conference (LAPC), 2018 Loughborough, IEEE, Loughborough, UK, November 12, 2018.
  • I. Saied, M. S. R. Bashri, and T. Arslan, “Wideband Textile Antenna for Monitoring Neurodegenerative Diseases,” IEEE Symposium on Personal, Indoor, and Mobile Radio Communications, Bologna, Italy, September 9, 2018.
  • 'Design of a Dual-Function Antenna for Microwave Gas Detection and Communication in Industrial Wireless Sensor Network Applications', CHAIRUNISSA C., Arslan T., The 2017 International Conference on Radar, Antenna, Microwave, Electronics and Telecommunications (ICRAMET), Jakarta/Indonesia. October 2017.
  • F.Wang and T.Aslan,"A Thinfilmbased Wearable Antenna Array for Breast Microwave Imaging and Diagnosis​",(Accepted) 2017.
  • F.Wang and T.Aslan, “A Wearable Ultra-Wideband Monopole Antenna with Flexible Artificial Magnetic Conductor,” in 2016 Loughborough Antennas & Propagation Conference (LAPC), Loughborough, 2016, pp. 514-518.
  • F.Wang, X.Wu and T.Aslan, “Mobile-Controlled Portable Robotic Measurement Setup for Microwave Imaging Diagnosis,” in 2016 Loughborough Antennas & Propagation Conference (LAPC), Loughborough, 2016, pp. 277-281.
  • F.Wang and T.Aslan, “Inkjet-Printed Antenna on Flexible Substrate for Wearable Microwave Imaging Applications,” in 2016 Loughborough Antennas & Propagation Conference (LAPC), Loughborough, 2016, pp. 188-191.
  • M. S. R. Bashri, T. Arslan and W. Zhou, "A Compact RF Switching System for Wearable Medical Imaging," 2016 Loughborough Antennas & Propagation Conference (LAPC), pp. 251-254, Loughborough, 2016.
  • M. S. R. Bashri, T. Arslan and W. Zhou, "A dual-band linear phased array antenna for WiFi and LTE mobile applications," 2015 Loughborough Antennas & Propagation Conference (LAPC), pp.175-179, Loughborough, 2015.
  • M. S. R. Bashri, T. Arslan, W. Zhou and N. Haridas, "Wearable Device for Microwave Head Imaging," European Microwave Conference (EuMC), pp. 671-674, 2016, London.
  • M. S. R. Bashri, T. Arslan and W. Zhou, "Flexible antenna array for wearable head imaging system," 2017 11th European Conference on Antennas and Propagation (EUCAP), Paris, 2017, pp. 172-176.
  • M. S. R. Bashri and T. Arslan, "Low-cost and compact RF switching system for wearable microwave head microwave head imaging with performance verification on artificial head phantom," IET Microwaves, Antenna & Propagation, 2017.
  • Ramli, N.A., Arslan, T., Haridas, N. et al. "Design, simulation and analysis of a digital RF MEMS varactor using thick SU-8 polymer," Microsystem Technology (2017), pp.1-10.
  • N. A. Ramli and T. Arslan, "Design and simulation of a 2-bit distributed S-band MEMS phase shifter," 2017 18th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE), Dresden, 2017, pp. 1-5.
  • N. A. Ramli, T. Arslan, N. Haridas and W. Zhou, "Design and modelling of a digital MEMS varactor for wireless applications," 2016 17th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE), pp.119-123, Montpellier, 2016.
  • N. A. Ramli, T. Arslan, N. Haridas and Wei Zhou, "Design and simulation of a high tuning range MEMS digital varactor using SU-8," 2016 Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (DTIP), pp. 73-78, Budapest, 2016.