Research project

AID-BCC (AI-Assisted diagnosis of Basal Cell Carcinoma)

Basal cell carcinoma is the most common form of skin cancer. This project investigates whether non-invasive, AI-assisted imaging can make the assessment of skin lesions more efficient. The aim is gentler and more resource-efficient diagnostics for future patients.

Basal cell carcinoma (BCC) is the most common type of skin cancer, accounting for approximately 80% of all skin cancer cases. Today, diagnosis typically relies on clinical examination, dermoscopy and biopsy. There is a growing need for non-invasive methods that can support lesion assessment and make the diagnostic pathway more efficient for patients.

The project examines the clinical usability of three advanced, non-invasive imaging techniques: optical coherence tomography (OCT), line-field confocal OCT (LC-OCT) and high-frequency ultrasound (HFUS). Each technique includes an integrated artificial intelligence (AI) module that can support image interpretation.

The study is prospective and observational and is conducted at the Department of Dermatology, Bispebjerg Hospital. The examinations are non-invasive and do not affect patients' subsequent treatment. The aim is to determine how long each method takes, how practical it is to use, how good the image quality is, and how well AI-assisted imaging agrees with histological findings.

Researcher

Physician and PhD student Otto Dideriksen

Project Supervisors

Professor and Chief Consultant Merete Hædersdal, MD, PhD, DMSc

Vinzent Kevin Ortner, MD, PhD

Kevin Jacobsen, MD, PhD

Peter Alshede Philipsen, MSc, PhD

Project period

2026 – 2028

Financing

Danish Research Center for Skin Cancer

Bispebjerg Hospital’s Internal Research Fund

Aage Bangs Fond

Selected publications

Dideriksen O, Jacobsen K, Untracht GR, Philipsen PA, Haedersdal M, Ortner VK. AI-Assisted Basal Cell Carcinoma Analysis in Line-Field Confocal OCT Exploring Diagnostic Metrics. J Biophotonics. 2026 Oct;19(10):e70374.