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Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks (1807.06489v1)

Published 17 Jul 2018 in cs.LG, physics.med-ph, and stat.ML

Abstract: 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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Authors (5)
  1. Rafid Mahmood (20 papers)
  2. Aaron Babier (8 papers)
  3. Andrea McNiven (2 papers)
  4. Adam Diamant (5 papers)
  5. Timothy C. Y. Chan (33 papers)
Citations (93)

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