Exploring the limit of image resolution for human expert classification of vascular ultrasound images in giant cell arteritis and healthy subjects: the GCA-US-AI project

• Published in: Annals of the rheumatic diseases
• Main Authors: Bauer, Claus-Juergen, Chrysidis, Stavros, Dejaco, Christian, Koster, Matthew J, Kohler, Minna J, Monti, Sara, Schmidt, Wolfgang A, Mukhtyar, Chetan B, Karakostas, Pantelis, Milchert, Marcin, Ponte, Cristina, Duftner, Christina, de Miguel, Eugenio, Hocevar, Alojzija, Iagnocco, Annamaria, Terslev, Lene, Døhn, Uffe Møller, Nielsen, Berit Dalsgaard, Juche, Aaron, Seitz, Luca, Keller, Kresten Krarup, Karalilova, Rositsa, Daikeler, Thomas, Mackie, Sarah Louise, Torralba, Karina, van der Geest, Kornelis S M, Boumans, Dennis, Bosch, Philipp, Tomelleri, Alessandro, Aschwanden, Markus, Kermani, Tanaz A, Diamantopoulos, Andreas, Fredberg, Ulrich, Inanc, Nevsun, Petzinna, Simon M, Albarqouni, Shadi, Behning, Charlotte, Schäfer, Valentin Sebastian
• Format: Journal Article
• Language: English
• Published: United States 12.06.2025
• ISSN: 1468-2060
• DOI: 10.1016/j.ard.2025.05.010

Prompt diagnosis of giant cell arteritis (GCA) with ultrasound is crucial for preventing severe ocular and other complications, yet expertise in ultrasound performance is scarce. The development of an artificial intelligence (AI)-based assistant that facilitates ultrasound image classification and h...