CORN-Complex

CORN-Complex is a large-scale, multi-center, multi-disease dataset designed to reflect real-world clinical complexity. It comprises 7,522 images from 518 patients across 12 distinct corneal pathologies. Data were collected from six clinical centers using two imaging systems: Confoscan 3.0 (resized to 384×384) and Heidelberg HRT-III/RCM (384×384). All images were exported directly from CCM devices without manual quality filtering to preserve the full spectrum of variability encountered in clinical practice. A representative subset of 1,429 images, ensuring balanced coverage of all disease categories, imaging devices, and clinical centers, was exhaustively annotated by two image analysis experts and reviewed by a senior ophthalmologist, providing high-quality ground truth labels for corneal nerves (CNs) and Langerhans cells (LCs). To ensure reliable benchmarking, we define a fixed data split: 5% of the total dataset (376 images) is allocated as the test set, with another 5% (376 images) reserved for validation. The remaining 6,770 images form the training pool, of which 10% (677 images) are labeled.

12 corneal pathologies: Fungal keratitis; Viral keratitis; Anterior Basement Membrane Dystrophy; Neurotrophic Keratitis; Nonspecific keratitis; Keratoconus; Fuchs endothelial dystrophy; Dry eye disease; Post-corneal surgery; Neuropathic corneal pain; Diabetes mellitus; Corneal endotheliitis.