Potential Graduate Study Supervisors

The following OMPI Members have openings in 2019 for M.Sc. or Ph.D. students. Click on their names for details on their research interests.

For general information on the medical physics program, contact the ompi_aaoatphysics [dot] carleton [dot] ca (OMPI Assistant Academic Officer).


  • Rob deKemp
    • Cardiac PET-CT blood flow quantification
    • Kinetic modeling for sympathetic innervation tracers
    • Cardiac PET-MR attenuation correction
    • Deep learning for diagnostic image interpretation
  • Paul Johns
    • x-ray scatter imaging
  • Ran Klein
    • Task-based optimization of PET-CT image reconstruction and display
    • Artificial intelligence based image segmentation and lesion detection
    • Lesion synthesis in PET and CT
    • Perception performance of human- and machine-observers
  • Sangeeta Murugkar
    • Using Raman spectroscopy to assess tumour sensitivity to treatment
    • Development of a nonlinear optical imaging technique for cancer detection
  • Pat Saull
    • Stand-off radiation detection and localization in the environment using Compton gamma imaging
    • Monte Carlo simulation of detector response for gamma imaging and beta dosimetry
    • Development of radiation detectors based on silicon photomultipliers
  • Laurel Sinclair
    • Long range characterization of radioactivity in the environment: (a) fieldable Compton imager, (b) novel UAV-mounted directional spectrometer
  • Glenn Wells
    • Cardiac pinhole SPECT - image reconstruction and performance assessment
    • Dynamic SPECT/CT imaging for measuring absolute blood flow in the heart


  • Elsayed Ali
    • Development and validation of different rapid-access palliative radiation therapy models.
    • Developments in cone beam CT for better geometric patient positioning, reduced imaging dose, and cone-beam-based radiation treatment planning.
    • Accurate dosimetric markers for radiation-induced early symptoms.
    • Auto-segmentation of the bowel bag using mathematical modelling and/or machine- and deep-learning methods.
    • Development and validation of Monte Carlo radiation transport methods for radiation measurements and dose calculations.
  • Emily Heath and Tong Xu
    • Motion-adaptive radiation therapy
  • Emily Heath and Joanna Cygler
    • Monte Carlo simulation of radiotherapy delivery incorporating patient-specific respiratory motion measurements
  • Malcolm McEwen
    • Using Monte Carlo techniques to investigate detector response
    • Modelling of dosimetry primary and secondary standards
  • Rowan Thomson 
    • Dosimetry and radiobiological modelling for radiotherapy
    • Simulations of low energy electron transport in biological media
    • Monte Carlo simulations for radiation interactions and energy deposition on cellular and subcellular scales: multiscale modelling