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arXiv Computer Vision By Benjamin Jin, Maria del C. Vald\'es Hern\'andez, Richard Bortsov, Joanna M. Wardlaw, Daniel Bos, Grant Mair

Automated Distinction of Intimal and Medial Intracranial Arterial Calcification from CT Head

Read the original on arXiv Computer Vision →

The study evaluates three automated methods for distinguishing intimal from medial intracranial arterial calcifications (IACs) on non‑contrast head CT scans. Using segmentation masks, the methods—an adapted visual score, a sphericity metric, and shape embeddings from a medical foundation model—achieved comparable performance, with the embedding approach achieving the highest weighted F1 scores (71.5% for single arteries, 59.8% for joint classification). The approach remains robust when using automated versus manual segmentation masks, demonstrating feasibility for fully automated IAC subtype quantification.

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