nnDoseNet: Intuitive and flexible deep learning framework to train and evaluate radiotherapy dose prediction models

Abstract

By offering automated data preprocessing, systematic model training, and robust dose evaluation all within a single framework nnDoseNet reduces the complexity of building and testing dose prediction models. It accommodates diverse prescription doses, organ-at-risk definitions, and hardware configurations, making it a suitable benchmark for multi-institutional research. With its balance of simplicity, flexibility, and performance, nnDoseNet aims to accelerate the development, comparison, and clinical integration of advanced AI-driven dose prediction methods in radiotherapy. Importantly, the nnDoseNet output is a dose prediction, not a clinically deliverable treatment plan. Plan optimization, QA, and clinical approval remain separate steps outside the scope of this work.

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