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SUMMARY:AI-based dose calculation in medical physics
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UID:indico-contribution-490-1969@events.ncbj.gov.pl
DESCRIPTION:Speakers: Julien Bert (CHRU Brest)\nMonte Carlo simulation has
  remained the “gold standard” for dose calculation in medical physics 
 since the 1970s\, providing highly accurate estimates of patient radiation
  exposure for applications ranging from diagnostic imaging to cancer treat
 ment such as radiotherapy.  Monte Carlo simulations model particle interac
 tions and follow the law of large numbers. Their inherently stochastic nat
 ure represents their main limitation\, as obtaining high-statistical-quali
 ty results requires substantial computation time. Over the past five decad
 es\, researchers have sought to improve efficiency through both algorithmi
 c innovations\, including variance-reduction techniques\, and advances in 
 computing hardware\, from early supercomputer parallelization to massively
  parallel GPU-based implementations in the 2010s. Today\, the emergence of
  Artificial Intelligence (AI) introduces new opportunities to drastically 
 accelerate Monte Carlo simulations by learning to approximate\, guide\, or
  emulate radiation transport while preserving physical accuracy. This pres
 entation focuses on these AI-driven strategies and examines how they enabl
 e fast\, and in some cases real-time\, radiation dose estimation across a 
 range of medical physics applications.\n\nhttps://events.ncbj.gov.pl/event
 /490/contributions/1969/
LOCATION:Zoom https://cern.zoom.us/j/66151941204?pwd=n7upvvZYibexBhbtyn5kv
 Tpy36L0Wo.1
URL:https://events.ncbj.gov.pl/event/490/contributions/1969/
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SUMMARY:Discussion
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UID:indico-contribution-490-1968@events.ncbj.gov.pl
DESCRIPTION:https://events.ncbj.gov.pl/event/490/contributions/1968/
LOCATION:Zoom https://cern.zoom.us/j/66151941204?pwd=n7upvvZYibexBhbtyn5kv
 Tpy36L0Wo.1
URL:https://events.ncbj.gov.pl/event/490/contributions/1968/
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