1. Machine-learning classification of non-melanoma skin cancers from image features obtained by optical coherence tomography

    Background/purpose: A number of publications have suggested that optical coherence tomography (OCT) has the potential for non-invasive diagnosis of skin cancer. Currently, individual diagnostic features do not appear sufficiently discriminatory. The combined use of several features may however be useful. Methods: OCT is based on infrared light, photonics and fibre optics. The system used has an axial resolution of 10 μm, lateral 20 μm. We investigated the combined use of several OCT features from basal cell carcinomas (BCC) and actinic keratosis (AK). We studied BCC (41) and AK (37) lesions in 34 consecutive patients. The diagnostic accuracy of the ...
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