Uncertainty-weighted and relation-driven consistency training for semi-supervised head-and-neck tumor segmentation

A deep learning-based semiautomated workflow for triaging follow-up MR scans in treated nasopharyngeal carcinoma

“…The strength of DL is the potential capacity of an assisted DL-based CAD tool to conserve resources and reduce oversights in the surveillance process among cancer survivors with treated NPC. Although there have been several studies assessing the stand-alone performance of CAD tool in detecting primary NPC tumor, 21 , 22 , 23 , 24 however, to date, there are no studies investigating DL-powered triaging approach in optimizing surveillance in survivors with cured NPC.…”