Cervical OCT image classification using contrastive masked autoencoders with Swin Transformer.

Background And Objective: Cervical cancer poses a major health threat to women globally. Optical coherence tomography (OCT) imaging has recently shown promise for non-invasive cervical lesion diagnosis. However, obtaining high-quality labeled cervical OCT images is challenging and time-consuming as they must correspond precisely with pathological results.