Moderator: Kevin Moore, UC San Diego
Moderator: Qing-Rong Jackie Wu, Duke University Medical Center
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| Tuesday
3:30 PM | TU-EF-TRACK 3-1 : BEST IN PHYSICS (THERAPY): Automated Proton Treatment Planning with Robust Optimization Using Constrained Hierarchical Optimization
V.Taasti*, L.Hong, J.Deasy, M.Zarepisheh |
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| Tuesday
3:38 PM | TU-EF-TRACK 3-2 : A Deep-Learning Method of Automatic VMAT Planning Via MLC Dynamic Sequence Prediction (AVP-DSP) Using 3D Dose Prediction: A Feasibility Study of Prostate Radiotherapy Application
Y.Ni*, J.Zhang, Y.Sheng, X.Li, J.Ye, Y.Ge,
Q.Wu, C.Wang |
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| Tuesday
3:46 PM | TU-EF-TRACK 3-3 : A Lightweight Deep-Learning Model for Automatic IMRT Planning Via Fluence Map Prediction with a 2.5D Implementation: A Study of Head-And-Neck IMRT Application
C.Wang*, X.Li, Y.Sheng, J.Zhang, K.Lafata, F.Yin,
Q.Wu, Y.Ge, Q.Wu |
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| Tuesday
3:54 PM | TU-EF-TRACK 3-4 : Automated Plan Check Software Using a Multi-Layered Rules and AI Based Approach
S.Luk*, L.Wootton, A.Kalet |
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| Tuesday
4:02 PM | TU-EF-TRACK 3-5 : Automation of Palliative Radiotherapy Treatment Planning Using Independent Models to Prevent Errors From Propagating Through the Planning Process
T.Netherton*, D.Rhee, C.Cardenas, C.Chung, A.Klopp, L.Colbert,
C.Nguyen, V.Kolluru, R.Douglas, C.Peterson, R.Howell,
P.Balter, L.Court |
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| Tuesday
4:10 PM | TU-EF-TRACK 3-6 : Fluence Map Prediction Using Deep Learning Models: A Pilot Study for AI-Driven Pancreas SBRT Planning
W.Wang*, Y.Sheng, J.Zhang, X.Li, P.Jensen, C.Wang,
F.Yin, Q.Wu, Y.Ge, Q.Wu |
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| Tuesday
4:18 PM | TU-EF-TRACK 3-7 : BEST IN PHYSICS (THERAPY): Insights Into Planning Techniques Mastered by An Autoplanning Robot: Can An AI Planning Agent Be Interpretable and Tractable?
J.Zhang*, C.Wang, Y.Sheng, F.Yin, Y.Ge, Q.Wu |
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| Tuesday
4:26 PM | TU-EF-TRACK 3-8 : Inter-Institutional Dose Prediction with Deep Convolutional Neural Network and Transfer Learning for Prostate Cancer VMAT Treatments
R.Norouzi-Kandalan*, D.Nguyen, M.Lin, A.Barragan Montero, S.Breedveld, k.Namuduri,
S.Jiang |
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| Tuesday
4:34 PM | TU-EF-TRACK 3-9 : Knowledge-Based Three-Dimensional Dose Prediction for Tandem-And-Ovoid Brachytherapy
K.Cortes*, A.Simon, K.Kallis, J.Mayadev, S.Meyers, K.Moore |
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| Tuesday
4:42 PM | TU-EF-TRACK 3-10 : Machine Learning for Lung SBRT Auto Planning and Clinical Decision Support
S.Zieminski*, H.Willers, F.Keane, M.Khandekar, Y.Wang |
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| Tuesday
4:50 PM | TU-EF-TRACK 3-11 : Optimization-Free Interactive Planning Framework
L.Ma*, M.Chen, X.Gu, W.Lu |
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| Tuesday
4:58 PM | TU-EF-TRACK 3-12 : Predicting Treatment Plans with Reinforcement Learning
A.Babier*, A.McNiven, T.Chan |
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| Tuesday
5:06 PM | TU-EF-TRACK 3-13 : Reinforcement Learning for Fast and Intelligent Radiation Therapy Optimization
W.Hrinivich*, J.Lee |
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| Tuesday
5:14 PM | TU-EF-TRACK 3-14 : Verification of the Machine Delivery Parameters of Treatment Plan Via Deep Learning
j.fan*, L.Xing, Y.Yang |
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| Tuesday
5:22 PM | TU-EF-TRACK 3-15 : Human Knowledge Augmented Deep Reinforcement Learning for Intelligent Automatic Radiotherapy Treatment Planning
C.Shen*, L.Chen, Y.Gonzalez, D.Nguyen, S.Jiang, X.Jia |
