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Dr. April Khademi

April Khademi
Assistant Professor
BEng, MASc, PhD, PEng

Areas of Academic Interest

Medical image analysis and machine learning

Artificial intelligence in medicine

Education

Year University Degree
2012 University of Toronto PhD
2006 Toronto Metropolitan University MASc
2004 Toronto Metropolitan University BEng

Courses Taught

Course Code Course
BME 632 Signals and Systems II
BME 872 Biomedical Image Analysis
BE 8105 Advanced Medical Image Analysis

Spotlight

When April Khademi began her master’s degree, the medical community wasn’t quite ready to embrace or adopt machine learning for medical images. Physicians during this time said the field “wouldn’t go anywhere.” Then, along came IBM Watson, the AI platform designed to compete against Jeopardy! champions, and health-care professionals opened their minds to the power of artificial intelligence. “Now, clinicians are embracing these technologies and looking forward to integrating it into their practice,” she says. “It has the potential to change the way medicine is practiced and ultimately improve the quality of care for patients.” 

Clinical applications come naturally to Khademi, whose experience in industry and commercialization helps make translation of machine learning algorithms for medical imaging a reality. Her automated MRI analysis algorithms detect new biomarkers for neurodegenerative diseases, and characterize breast cancers in digital pathology images – work that, up until recently, was manually done using only a microscope. The result is faster, more objective diagnoses, fewer mistakes and, overall, higher quality of care.

Khademi brings that same industrial focus to her teaching, which relies heavily on design-based labs and practical implementation. Her teaching philosophy is encapsulated by the wise words of Albert Einstein: “Learning is experience. Everything else is just information.”

 April's Twitter Profile (external link) 

April Khademi

“Using technology in medicine to help people and serve a greater good in society is what drives me – every single day.”

  • Google Canada and Anita Borg Scholar Award
  • NSERC Alexander Graham Bell Doctoral Scholarship (CGSD)
  • Governor General’s Gold Medal
  • L'Oréal-UNESCO for Women in Science Scholarship
  • A. Khademi, B.Reiche*, J. DiGregorio*, G. Arezza*, A.R.Moody. “Multi-Centre, Multi-Disease Brain Extraction for FLAIR MRI”. Magnetic Resonance Imaging 
  • J. Pontalba, T. Gwynne, E. David, K. Jakate, D. Androutsos, A. Khademi. “Assessing the Need for Colour Normalization in Convolutional Neural Network-Based Nuclei Segmentation Frameworks”, Frontiers in Bioengineering and Biotechnology
  • R. S. Geread*, P. Morreale*, B. Dony, E.Bouwer, G. Wood, D. Androutsos, A. Khademi,  “IHC Colour Histograms for Unsupervised Ki67 Proliferation Index Calculation”, Frontiers in Bioengineering and Biotechnology
  • S. Duchesne, I. Chouinard, O. Potvin, V. Fonov, A. Khademi, R. Bartha, P. Bellec, D. Louis Collins, M. Descoteaux, R. Hoge, C. R. McCreary, J. Ramirez, C. J.M. Scott, E. E. Smith, S. C. Strother, and Sandra E. Black, for the CIMA-Q group and the CCNA group. “The Canadian Dementia Imaging Protocol: Harmonizing National Cohorts”. Journal of Magnetic Resonance Imaging. 49(2), pp.456-465, Feb. 2019.
  • O. Commowick , A. Istace , M. Kain , B. Laurent , F. Leray, M. Simon, S. Camarasu Pop, P. Girard, R. Améli, J-C Ferré, A. Kerbrat, T. Tourdias, F. Cervenansky, T. Glatard, J. Beaumont, S. Doylei, F. Forbes, J. Knight*, A. Khademi, A. Mahbod, C. Wang, R. McKinley, F. Wagner, J. Muschelli, E. Sweeney, E. Roura, X. Lladó, M.M. Santos, W.P. Santos, A.G. Silva-Filhoq, X. Tomas-Fernandezs, H. Urient, I. Blocht, S. Valverdep, M. Cabezas, F. Javier Vera-Olmos, N. Malpica, C. Guttmann, S. Vukusic, G. Edan, M. Dojat, M. Styner, S. K. Warfield, F. Cotton, C. Barillot, “Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure”, Nature Scientific Reports, 8(13650), pp1-17, Sept. 2018