Deep learning dose prediction for IMRT of esophageal cancer: The effect of data quality and quantity on model performance

PurposeTo investigate the effect of data quality and quantity on the performance of deep learning (DL) models, for dose prediction of intensity-modulated radiotherapy (IMRT) of esophageal cancer.Material and methodsTwo databases were used: a variable database (VarDB) with 56 clinical cases extracted retrospectively, including user-dependent variability in delineation and planning, different machines and beam configurations; and a homogenized...