{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/automated-treatment-planning-in-radiation","title":"Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks","arxiv_id":"1807.06489","date":"2018-07-17","proceeding":null,"authors":["Rafid Mahmood","Aaron Babier","Andrea McNiven","Adam Diamant","Timothy C. Y. Chan"],"abstract":"Knowledge-based planning (KBP) is an automated approach to radiation therapy\ntreatment planning that involves predicting desirable treatment plans before\nthey are then corrected to deliverable ones. We propose a generative\nadversarial network (GAN) approach for predicting desirable 3D dose\ndistributions that eschews the previous paradigms of site-specific feature\nengineering and predicting low-dimensional representations of the plan.\nExperiments on a dataset of oropharyngeal cancer patients show that our\napproach significantly outperforms previous methods on several clinical\nsatisfaction criteria and similarity metrics.","url_abs":"http://arxiv.org/abs/1807.06489v1","url_pdf":"http://arxiv.org/pdf/1807.06489v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"automated-treatment-planning-in-radiation","repo_url":"https://github.com/rafidrm/gancer","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"feature-engineering","task_name":"Feature Engineering"},{"task_slug":null,"task_name":"Generative Adversarial Network"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}