AAPM supports the Medical Physics community with a focus on advancing patient care. Be there and meet with us at RaySearch to see the latest developments in oncology software.
At this year’s AAPM, RaySearch is putting a strong focus on machine learning and automation in radiation oncology. Some exciting news in these areas will be on display like deep-learning segmentation* and machine learning based automated planning*. We will also present the latest news in our advanced treatment planning system RayStation and the next-generation OIS RayCare*. Come by booth #600 to hear more. Book your demo today!
*Subject of regulatory clearance in some markets
PRESENTATIONS
Tuesday, July 16 | 7:30 am–9:30 am
Room: Stars at Night Ballroom
FIRST REPORT ON METHODOLOGY DEVELOPMENT AND VALIDATION OF LET COMPUTED IN A MONTE CARLO DOSE ENGINE OF A COMMERCIAL TREATMENT PLANNING SYSTEM
D Wagenaar1*, T Tran2, A Meijers1, D Bolst2, B James2,
M Povoli3, A Kok3, E Traneus4, M van Goethem1,
J Langendijk1, A Rosenfeld2, S Both1,
(1) University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
(2) University of Wollongong, Wollongong, Australia
(3) SINTEF, Oslo, Norway
(4) RAYSEARCH LABORATORIES AB, Stockholm, Sweden
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PARTNERS IN SOLUTIONS
Wednesday, July 17 | 10:15 am–12:00 pm
Room: Speaker ready room 224
SCRIPTING, SO MUCH MORE THAN CODE
Cameron Ditty, M.S. Senior Physics Specialist,
RaySearch Americas Inc. subsidiary of RaySearch Labs (AB)
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E-POSTER PRESENTATIONS
Sunday, July 14 | 12:30 pm–17:00 pm
Room: ePoster Forums
THE APPLICATION OF FALLBACK PLANNING IN IMPT FOR
HEAD AND NECK CANCERS
Haijiao Shang, RaySearch Labs; Yuenan Wang, CAMS Shenzhen Cancer Hospital
Tuesday, July 16 | 9:30 am–10:00 am
TU-C930-GePD-F9-1, Exhibit Hall | Forum 9
AUTOMATIC SEGMENTATION ON CBCT IMAGES USING A COMBINATION OF CBCT ENHANCEMENT AND DEEP LEARNING CT SEGMENTATION
Sebastian Andersson*, Rasmus Nilsson,
RaySearch Laboratories, Stockholm, Sweden
Wednesday, July 17 | 9:30 am–10:00 am
WE-C930-GePD-F8-3, Exhibit Hall | Forum 8
INTERACTIVE DEEP LEARNING-BASED DELINEATION OF GROSS
TUMOR VOLUME FOR POST-OPERATIVE GLIOMA PATIENTS
M Nordstrom1,2*, J Soderberg2, N Shusharina3, D Edmunds3, F Lofman2, H Hult1, A Maki1, T Bortfeld3,
(1) Royal Institute of Technology, Stockholm,
(2) RaySearch Laboratories, Stockholm,
(3) Massachusetts General Hospital, Boston
