Automated plan generation for prostate radiotherapy patients using deep learning and scripted optimization
Background and Purpose: Treatment planning is a time-intensive task that could be automated. We aimed to develop a “single-click” workflow, fully deployed within a commercial treatment planning system (TPS), for autoplanning prostate radiotherapy treatment plans using predictions from a deep learnin...
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Main Authors: | Cody Church, Michelle Yap, Mohamed Bessrour, Michael Lamey, Dal Granville |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2024-10-01
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Series: | Physics and Imaging in Radiation Oncology |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2405631624001118 |
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