Robust CTA lumen segmentation of the atherosclerotic carotid artery bifurcation in a large patient population

Rashindra Manniesing, Michiel Schaap, Sietske Rozie, Krijn Hameeteman, Danijela Vukadinovic, Aad van der Lugt, Wiro Niessen

Research output: Contribution to journalArticleAcademic

35 Citations (Scopus)

Abstract

We propose and validate a semi-automatic method for lumen segmentation of the carotid bifurcation in computed tomography angiography (CIA). First, the central vessel axis is obtained using path tracking between three user-defined points. Second, starting from this path, the segmentation is automatically obtained using a level set. The cost and speed functions for path tracking and segmentation make use of intensity and homogeneity slice-based image features. The method is validated on a large data set of 234 carotid bifurcations of 129 ischemic stroke patients with atherosclerotic disease. The results are compared to manually obtained lumen segmentations. Parameter optimization is carried out on a subset of 30 representative carotid bifurcations. With the optimized parameter settings the method successfully tracked the central vessel paths in 201 of the remaining 204 bifurcations (99%) which were not part of the training set. Comparison with manually drawn segmentations shows that the average overlap between the method and observers is similar (for the inter-observer set the results were 92% vs. 87% and for the intra-observer set 94% vs. 94%). Therefore the method has potential to replace the manual procedure of lumen segmentation of the atherosclerotic bifurcation in CTA. (c) 2010 Elsevier B.V. All rights reserved.
Original languageUndefined/Unknown
Pages (from-to)759-769
Number of pages11
JournalMedical Image Analysis
Volume14
Issue number6
DOIs
Publication statusPublished - 2010

Cite this