Abstract Objective: The aim of this study was to develop and validate a cascaded artificial intelligence (AI) framework using a segmentation–discrimination strategy for automated detection of ossicular chain malformations (OCM) on computed tomography scans. Methods: Patients diagnosed with OCM between January 2009 and January 2023, along with healthy controls, were retrospectively enrolled. A coarse-to-fine nnU-Net framework was applied for automated segmentation of the auditory ossicles.
