A hybrid Transformer-UNet model with energy-shifting inputs generates 6 MV LINAC dose maps from monoenergetic data, achieving over 98% gamma passing rate (3%/3mm) versus full Monte Carlo for prostate radiotherapy.
A review on low-dose emission tomography post-reconstruction denoising with neural network approaches
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A fast and Generic Energy-Shifting Transformer for Hybrid Monte Carlo Radiotherapy Calculation
A hybrid Transformer-UNet model with energy-shifting inputs generates 6 MV LINAC dose maps from monoenergetic data, achieving over 98% gamma passing rate (3%/3mm) versus full Monte Carlo for prostate radiotherapy.