TransAnaNet: Transformer-based Anatomy Change Prediction Network for Head and Neck Cancer Patient Radiotherapy

arXiv:2405.05674v1 Announce Type: new
Abstract: Early identification of head and neck cancer (HNC) patients who would experience significant anatomical change during radiotherapy (RT) is important to optimize patient clinical benefit and treatment resources. This study aims to assess the feasibility of using a vision-transformer (ViT) based neural network to predict RT-induced anatomic change in HNC patients. We retrospectively included 121 HNC patients treated with definitive RT/CRT. We collected the planning CT (pCT), planned dose, CBCTs acquired at the initial treatment …

abstract arxiv benefit cancer change clinical cs.cv experience head identification network patient patients physics.med-ph prediction resources study transformer treatment type vision vision-transformer vit