Farah Deeba, Ph.D.

Dr. Farah Deeba, Ph.D.

Assistant Professor
Electrical & Computer Engineering
Education and Training:
  • Ph.D., The University of British Columbia, Vancouver, Canada, 2022
  • M.Sc., University of Saskatchewan, Saskatchewan, Canada, 2016
  • B.Sc., Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, 2013
Research Areas:
  • Medical Imaging
  • Placenta Tissue Imaging and Characterization
  • Quantitative Ultrasound
  • Signal Processing
  • Machine Learning
Selected Publications:

1. Deeba, F., Schneider, C., Mohammed, S., Honarvar, M., Lobo, J., Tam, E., Salcudean, S. and Rohling, R., 2021. A multiparametric volumetric quantitative ultrasound imaging technique for soft tissue characterization. Medical Image Analysis, 74, p.102245.

2. Deeba, F., Hu, R., Lessoway, V., Terry, J., Pugash, D., Mayer, C., Hutcheon, J., Salcudean, S. and Rohling, R., 2022. Project SWAVE 2.0: An overview of the study design for multimodal placental image acquisition and alignment. MethodsX, p.101738.

3. Deeba, F. and Rohling, R., 2019, October. PredictUS: A Method to Extend the Resolution-Precision Trade-Off in Quantitative Ultrasound Image Reconstruction. In International Workshop on Machine Learning for Medical Image Reconstruction (pp. 255-264). Springer, Cham.

4. Deeba, F., Ma, M., Pesteie, M., Terry, J., Pugash, D., Hutcheon, J.A., Mayer, C., Salcudean, S. and Rohling, R., 2019. Attenuation coefficient estimation of normal placentas. Ultrasound in medicine & biology, 45(5), pp.1081-1093.

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