3 papers
cs.CV2026
Robustness of Transformer-Based Fluence Map Prediction Under Clinically Realistic Perturbations
Ujunwa Mgboh, Rafi Ibn Sultan, Joshua Kim +2
Learning-based fluence map prediction offers a fast alternative to iterative inverse planning in intensity-modulated radiation therapy (IMRT), but its robustness under realistic di…
cs.CV2026
FluenceFormer: Transformer-Driven Multi-Beam Fluence Map Regression for Radiotherapy Planning
Ujunwa Mgboh, Rafi Ibn Sultan, Joshua Kim +2
Fluence map prediction is central to automated radiotherapy planning but remains an ill-posed inverse problem due to the complex relationship between volumetric anatomy and beam-in…
eess.IV2025
Fluence Map Prediction with Deep Learning: A Transformer-based Approach
Ujunwa Mgboh, Rafi Sultan, Dongxiao Zhu +1
Accurate fluence map prediction is essential in intensity-modulated radiation therapy (IMRT) to maximize tumor coverage while minimizing dose to healthy tissues. Conventional optim…