Automatic segmentations for carotid vessel lumen and wall with arterial calcifications using spatially registered black- and gray-blood images

We investigated automatic segmentations for the carotid vessel lumen and wall with the presence of arterial calcifications using spatially registered black- and gray-blood images. CS-siBLAG sequence was used to provide black- and gray-blood images. A K-means algorithm was employed to segment carotid artery lumen on black-blood images and calcifications on gray-blood images. A distance transform and an active contours model was used to segment the vessel wall. This method improves lumen segmentation, since it avoids the over-segmentation of vessel lumen by means of subtracting calcifications obtained on gray-blood images from the vessel lumen segmentation obtained on black-blood images.