Researchers at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) have developed a new method that combines Line-Field Confocal Optical Coherence Tomography (LC-OCT) with artificial intelligence to detect basal cell carcinoma (BCC) at an early stage. BCC is the most common form of skin cancer, and early detection is crucial for effective treatment.
LC-OCT is a non-invasive imaging technique that provides high-resolution, three-dimensional images of the skin at cellular level. By integrating AI-assisted image recognition, the system can automatically analyze these images and identify malignant changes that might be missed by the human eye. This approach aims to improve diagnostic accuracy and reduce the need for invasive biopsies.
The research, published in a peer-reviewed journal, demonstrates that the AI-enhanced LC-OCT method can distinguish BCC from healthy skin with high sensitivity and specificity. The team trained the AI on a large dataset of LC-OCT images, enabling it to recognize characteristic patterns of BCC. This could lead to faster, more reliable diagnoses in clinical practice.
While further validation is needed, this advancement represents a promising step toward AI-assisted dermatology. It could ultimately help clinicians detect skin cancers earlier and more accurately, improving patient outcomes. The researchers are now working on expanding the technology to other types of skin lesions.
