Quantifying the calcification of abdominal aorta and major side branches with deep learning.

Aim: To explore the possibility of a neural network-based method for quantifying calcifications of the abdominal aorta and its branches.

Materials And Methods: In total, 58 computed tomography (CT) angiography volumes were selected from a dataset of 609 to represent different stages of sclerosis. The ground truth segmentations of the abdominal aorta, coeliac trunk, superior mesenteric artery, renal arteries, common iliac arteries, and their calcifications were delineated manually.