Volumetric modulated arc therapy dose prediction and deliverable treatment plan generation for prostate cancer patients using a densely connected deep learning model
Background and purpose: Radiation therapy treatment planning is a manual, time-consuming task that might be accelerated using machine learning algorithms. In this study, we aimed to evaluate if a triplet-based deep learning model can predict volumetric modulated arc therapy (VMAT) dose distributions...
Main Authors: | Michael Lempart, Hunor Benedek, Christian Jamtheim Gustafsson, Mikael Nilsson, Niklas Eliasson, Sven Bäck, Per Munck af Rosenschöld, Lars E. Olsson |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2021-07-01
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Series: | Physics and Imaging in Radiation Oncology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405631621000439 |
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