Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks
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Abstract (arXiv)
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.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Jul 2018.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 4; 2024: 1; 2025: 0; 2026: 2.
11 papers.
- 2021Data synthesis and adversarial networks: A review and meta-analysis in cancer imagingcited by 15
- 2023DiffDP: Radiotherapy Dose Prediction via a Diffusion Modelcited by 13
- 2023Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encodingcited by 5
- 2022Learning Image Representations for Content Based Image Retrieval of Radiotherapy Treatment Planscited by 2
- 2022Improved α-GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planningcited by 2
- 2023SP-DiffDose: A Conditional Diffusion Model for Radiation Dose Prediction Based on Multi-Scale Fusion of Anatomical Structures, Guided by SwinTransformer and Projectorcited by 2
- 2024Triplet-constraint Transformer with Multi-scale Refinement for Dose Prediction in Radiotherapycited by 1
- 2021Site-Agnostic 3D Dose Distribution Prediction with Deep Learning Neural Networkscited by 0
- 2023Polymerized Feature-based Domain Adaptation for Cervical Cancer Dose Map Predictioncited by 0
- 2026DoseBridge: Denoising Diffusion Bridge Model for Dose Prediction in Lung Intensity-Modulated Proton Therapycited by 0
- 2026Dose-PlanNet: Physics Based Radiotherapy Dose Prediction with Deep Learningcited by 0
- 2026Dose-PlanNet: Physics Based Radiotherapy Dose Prediction with Deep Learning27 Aug 2026
- 2026DoseBridge: Denoising Diffusion Bridge Model for Dose Prediction in Lung Intensity-Modulated Proton Therapy10 Aug 2026
- 2024Triplet-constraint Transformer with Multi-scale Refinement for Dose Prediction in Radiotherapy7 Feb 2024
- 2023SP-DiffDose: A Conditional Diffusion Model for Radiation Dose Prediction Based on Multi-Scale Fusion of Anatomical Structures, Guided by SwinTransformer and Projector11 Dec 2023
- 2023Diffusion-based Radiotherapy Dose Prediction Guided by Inter-slice Aware Structure Encoding6 Nov 2023
- 2023Polymerized Feature-based Domain Adaptation for Cervical Cancer Dose Map Prediction20 Aug 2023
- 2023DiffDP: Radiotherapy Dose Prediction via a Diffusion Model19 Jul 2023
- 2022Improved α-GAN architecture for generating 3D connected volumes with an application to radiosurgery treatment planning13 Jul 2022
- 2022Learning Image Representations for Content Based Image Retrieval of Radiotherapy Treatment Plans6 Jun 2022
- 2021Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging20 Jul 2021
- 2021Site-Agnostic 3D Dose Distribution Prediction with Deep Learning Neural Networks15 Jun 2021