Ultrasound
Giant Cell Arteritis Ultrasound Dataset (GCA-US)
In-house ultrasound dataset of temporal and axillary artery scans with expert annotations of hypoechoic wall thickening, intima–media thickness and final clinical diagnosis.
Access
On request
Size
3,800 exams from 344 patients · expanded to ~15,000 images
Collected at
Research themes
Curated with the Center for Rare Rheumatological Diseases (Claus-Jürgen Bauer, Prof. Valentin Schäfer), University Hospital Bonn. One of the largest clinically validated datasets for ultrasound-based GCA diagnosis; being extended towards a multi-center German cohort.
Our lab led the ML-readiness: quality control, cleaning, standardised preprocessing, annotation workflow and training/validation splits.
Related publications
Entwicklung einer künstlichen Intelligenz zur ultraschallgestützten Detektion der Riesenzellarteriitis
Deutscher Rheumatologiekongress 2026 (DGRh) — German Medical Science, 2026
OP0343 The ClaudicAItio Model: Ultrasound Image Classification in Giant Cell Arteritis by Application of Artificial Intelligence
EULAR 2025 European Congress of Rheumatology — Annals of the Rheumatic Diseases 84 (Suppl.), 279–280, 2025