Stephen Pistorius, PhD, PPhys, FCOMP

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Stephen Pistorius, PhD, PPhys, FCOMP

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Research Discipline(s): Medical Physics

Primary Title: Professor

Additional Titles & Affiliations: Associate Head: Physics & Astronomy


Breast Microwave Imaging, PET & CT Scatter Imaging, Portal Imaging & Dosimetry

Our goal is to improve access to breast cancer screening in low and middle income countries and remote northern communities in Canada.

Research Summary

  1. Medical Devices for Microwave Breast Cancer Detection: My group is internationally recognized as a pioneer in experimental (as opposed to simulated) research in microwave-based Breast Cancer detection. We have developed, evaluated and licensed a Class 3 Health Canada medical device for microwave breast cancer imaging and are currently constructing a novel portable breast cancer detection system to enable some of the inequities associated with breast cancer screening to be addressed. To test these systems, we have created temporally consistent, dielectrically appropriate, and morphologically accurate MRI based breast phantoms using 3D printing and have been able to demonstrate that we can detect sub-cm breast lesions.
  2. Machine Learning for Breast Cancer Detection: We have been early adopters of machine learning for microwave-based breast cancer detection and have illustrated that this approach has a sensitivity and specificity equivalent to that of x-ray mammography, and as a result, opens up the opportunity to provide quick and accurate readerless detection of early-stage breast cancer.
  3. Microwave Image Reconstruction: We have patented and made significant improvements in algorithmic microwave imaging reconstructions over the years. Each of our papers showed significant improvements over the existing reconstruction approaches at the time. Our most recent radar-based reconstruction algorithm, which is arguably the most accurate microwave radar breast cancer algorithm to date, enables the physical attributes of the system, such as the antenna beam pattern, propagation speed, and microwave attenuation, to be taken into account.
  4. We have a decade long program investigating algebraic and machine learning approaches to scatter imaging in CT and PET, and hold two patents for this work.


My research focuses on developing novel tools and techniques for improved diagnostic and therapeutic cancer imaging and optimized oncology treatments, with a particular emphasis on approaches that can address the inequalities faced by marginalized and under-serviced populations in rural communities and low middle-income countries. I strive to inspire and provide opportunities to students of all ages, genders, and nationalities to become involved in research, and many of my previous students now serve in Medical Physics leadership positions.

Research Biography

Dr. Stephen Pistorius is a tenured Professor and Associate Head: Medical Physics in Physics and Astronomy, a Professor in Radiology at the University of Manitoba, and a Senior Scientist at the CancerCare Manitoba Research Institute.

He holds a B.Sc. (Physics & Geography), Hons. B.Sc. (Radiation Physics), M.Sc. (Medical Physics) and Ph.D. (Physics) degrees as well as a post-graduate diploma in Business Administration. He has leadership experience in the military, in industry, in clinical health care, as a senior administrator and in academia. He is a certified Medical Physicist, a licensed Professional Physicist, a senior member of the IEEE, and a Fellow of the Canadian Organization of Medical Physics (COMP).

Dr. Pistorius has served as the Treasurer and President of COMP and as the Director of Professional Affairs and President of the Canadian Association of Physicists. He has been the Director of the CAMPEP accredited Medical Physics graduate program at the University of Manitoba for many years and was and Vice Director and Graduate Chair of the U.M. Biomedical Engineering Graduate Program for over a decade. He has held several national grants, has contributed to over 300 publications and presentations, is currently supervising eight trainees and collaborates with and supports many more.

He believes in a collaborative approach to research, and ensures that their research outcomes are transparent and available to all by publishing the details of their research, including methods, code, and results in open access forums, such as at Active collaboration with colleagues in the Faculties of Science, Engineering, and Medicine at the University of Manitoba (U.M.), as well as in the U.S., UK, Ireland, South Africa, India, Nigeria and Portugal, has led to the involvement and support of numerous undergraduate and graduate students and post-doctoral fellows involved in improving cancer treatment outcomes through the application of megavoltage portal imaging, x-ray computed tomography, positron emission tomography, ultrasound, microwave imaging and various image processing techniques, including applications of Machine Learning. His leadership and involvement in these collaborations has been crucial to their ability to obtain grants and has led to many student awards and recognitions.


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    Featured Publications

    • R. C. Conceição et al., “Classification of breast tumor models with a prototype microwave imaging system,” Medical Physics., vol. 47, no. 4, pp. 1860–1870, Apr. 2020, doi: 10.1002/mp.14064.
    • T. Reimer, M. Solis-Nepote, and S. Pistorius, “The Application of an Iterative Structure to the Delay-and-Sum and the Delay-Multiply-and-Sum Beamformers in Breast Microwave Imaging,” Diagnostics, vol. 10, no. 6, p. 411, Jun. 2020, doi: 10.3390/diagnostics10060411.
    • T. Reimer, J. Krenkevich, and S. Pistorius, “An Open-Access Experimental Dataset for Breast Microwave Imaging,” in 2020 14th European Conference on Antennas and Propagation (EuCAP), Mar. 2020, pp. 1–5. doi: 10.23919/EuCAP48036.2020.9135659.
    • T. P. Teo et al., “Feasibility of predicting tumor motion using online data acquired during treatment and a generalized neural network optimized with offline patient tumor trajectories,” Medical Physics, vol. 45, no. 2, pp. 830–845, 2018, doi: 10.1002/mp.12731.
    • M. Ostadrahimi et al., “Analysis of Incident Field Modeling and Incident/Scattered Field Calibration Techniques in Microwave Tomography,” IEEE Antennas and Wireless Propagation Letters, vol. 10, pp. 900–903, 2011, doi: 10.1109/LAWP.2011.2166849.
    • G. Thomas, D. Flores-Tapia, and S. Pistorius, “Histogram Specification: A Fast and Flexible Method to Process Digital Images,” IEEE Transactions on Instrumentation and Measurement, vol. 60, no. 5, pp. 1565–1578, May 2011, doi: 10.1109/TIM.2010.2089110.
    • C. Gilmore et al., “A Wideband Microwave Tomography System With a Novel Frequency Selection Procedure,” IEEE Transactions on Biomedical Engineering, vol. 57, no. 4, pp. 894–904, Apr. 2010, doi: 10.1109/TBME.2009.2036372.
    • B. M. C. McCurdy, K. Luchka, and S. Pistorius, “Dosimetric investigation and portal dose image prediction using an amorphous silicon electronic portal imaging device,” Medical Physics, vol. 28, no. 6, pp. 911–924, 2001, doi: 10.1118/1.1374244.

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