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Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks

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arxiv 1807.06489 v1 pith:IMQN65RY submitted 2018-07-17 cs.LG physics.med-phstat.ML

classification cs.LGphysics.med-phstat.ML
keywords approachplanningpredictingtreatmentadversarialautomateddesirablegenerative
verification ladder T0 review T1 audit T2 compute T3 formal
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Knowledge-based planning (KBP) is an automated approach to radiation therapy treatment planning that involves predicting desirable treatment plans before they are then corrected to deliverable ones. We propose a generative adversarial network (GAN) approach for predicting desirable 3D dose distributions that eschews the previous paradigms of site-specific feature engineering and predicting low-dimensional representations of the plan. Experiments on a dataset of oropharyngeal cancer patients show that our approach significantly outperforms previous methods on several clinical satisfaction criteria and similarity metrics.

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