Basal cell carcinoma (BCC) is the most common cancer in humans. Up to now, these skin tumors have been detected relatively late clinically and by reflected light microscopy, so that they often require extensive surgery by means of micrographic surgery. The optical coherence tomography (OCT) is a non-invasive diagnostic tool for the early detection of subclinical BCC. Small BCC can be treated with a Nd:YAG laser instead of surgery instead of surgery.

In the OCTOLAB project, optical coherence tomography (OCT) for the diagnosis of basal cell carcinoma (BCC) will be integrated with a long-pulsed infrared laser for the therapy of BCC. In addition, diagnostics and therapy will be based on artificial intelligence (AI). AI will not only determine image parameters in the OCT images for the diagnosis of BCC including tumor thickness, tumor size, and subtype, but also control the laser therapy in terms of energy density, pulse length, and repetition rate, and finally verify the therapy success. This combined device for automated diagnostics and therapy could contribute to early detection and individualized minimally invasive therapy of BCC.