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Machine learning and automation in radiation oncology

20 Aug 2018 Sponsored by RaySearch Laboratories

Fredrik Löfman is head of machine learning at RaySearch Laboratories and holds a PhD in optimization of radiation therapy from Royal Institute of Technology, Stockholm. Prior to working with machine learning for oncology Fredrik has been part of developing the treatment planning system RayStation and, in particular, the multi-criteria optimization functionality.

Dr Thomas Purdie graduated from McMaster University, Hamilton, Ontario, Canada with a BSc (Hons) in the medical and health physics programme of the Department of Physics and Astronomy in 1997. He then completed his PhD in the Department of Medical Biophysics at the University of Western Ontario in London, Ontario in 2002. Following graduate school, he completed a medical physics residency and research fellowship at Princess Margaret Hospital (Toronto, Ontario) in 2005. He is currently a staff physicist in the radiation medicine programme at Princess Margaret Cancer Centre and became a board-certified medical physicist (CCPM – Radiation Therapy Physics) in 2007. He is an associate professor in the Department of Radiation Oncology, University of Toronto and affiliated faculty at the Techna Institute, University Health Network. Dr Purdie’s research focuses on developing methods for automated breast treatment planning and machine learning based treatment planning as well as machine learning for quality assurance (QA) processes in radiation oncology.

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