|
| Sunday | SU-H300-GePD-F6-1 : Deep Learning Based Surface Region-Of-Interest Selection for Motion Monitoring in Left Breast Cancer DIBH Radiotherapy
H.Chen, X.Zhen, L.Zhou, M.Chen, W.Lu, S.Jiang,
X.Gu* |
|
| Sunday | SU-H300-GePD-F6-2 : Deep Learning-Driven Target Volume Delineation for Prostate Cancer Radiation Therapy
Y.Wu*, A.Hsu, N.Kovalchuk, B.Han, L.Wang, Y.Rong,
L.Xing |
|
| Sunday | SU-H300-GePD-F6-3 : Development of An Automatic Deep Learning Framework for the Detection of Fiducial Markers in Intrafraction Kilovoltage Images
A.Mylonas*, P.Keall, J.Booth, T.Eade, D.Nguyen |
|
| Sunday | SU-H300-GePD-F6-4 : Enhancing Accuracy of the Deformation-Driven CBCT Reconstruction by a Deep Learning-Based Projection Mapping Scheme
Y.Zhang*, L.Chen, B.Li, M.Folkert, X.Jia, X.Gu,
J.Wang |
|
| Sunday | SU-H300-GePD-F6-5 : Prediction of Post-Radiotherapy Residual Disease From Pre-Treatment Imaging Using Deep Learning
D.Huff*, T.Bradshaw, R.Jeraj |
|
| Sunday | SU-H300-GePD-F6-6 : Quantifying the Dose to Functional Lung Regions Using Patient-Specific Elasticity Distributions Estimated From a Deep Learning Approach
K.Hasse*, D.O'Connell, J.Neylon, Y.Min, P.Lee, D.Low,
A.Santhanam |
