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Our paper ” RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy via Deep Learning” was editor’s pick in the ESTRO news letter.

In this paper, we have replaced the time consuming Mone Carlo method  for use in brachytherapy dose calculations with a 3-dimensional deep convolutional neural network model to provide fast and accurate dose estimations. The work by Ximeng Mao during his master’s studies at the Enger Lab and in collaboration with Dr. Joelle Pineau allows for dose simulations that are as accurate as the gold-standard Monte-Carlo methods but take much less time. A brief discription of the RapidBrachyDL has become the editor’s pick in ESTRO news letter. More …

Our paper ” RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy via Deep Learning” was editor’s pick in the ESTRO news letter. Read More »

McMedHacks – Mentorship in Action

McMedHacks COMP interactions

Our new McMedHacks workshop series and hackathon were recently featured in the renowned COMP InterACTIONS Journal. You can read the full article here: https://console.virtualpaper.com/canadian-organization-of-medical-physicists/interactions-october-2021/#28/ McMedHacks was an initiative started by our AI Group to bridge the domains of medical physics and deep learning in the field of medical image analysis. The program is free and …

McMedHacks – Mentorship in Action Read More »

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