Neural network assessment of aortic, iliac, renal, and mesenteric artery calcification in CTA: Normalized scoring framework and comparison to threshold-based method.

Key Points

• The aim is to develop a deep learning tool for assessing calcification in major abdominal arteries.
• Development of a deep learning neural network model
• Quantification of calcification in aortic, iliac, renal, and mesenteric arteries
• Comparison with manual and threshold-based scoring methods
• The deep learning tool provides fast and reproducible quantification
• Offers observer-independent results compared to manual methods
• Demonstrated potential for improved scoring accuracy in abdominal artery assessment

Abstract