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Cerebral Arteries: Fully Automated Segmentation from CT Angiography—A Feasibility Study¹

¹ From the Departments of Medical Informatics (R.M., W.J.N.) and Radiology (R.M., A.v.d.L., W.J.N.), Erasmus MC–University Medical Center Rotterdam, Dr. Molewaterplein 40/50, 3015 GE Rotterdam, the Netherlands; and Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands (M.A.V.). From the 2006 RSNA Annual Meeting. Received March 15, 2007; revision requested May 23; revision received July 16; accepted August 16; final version accepted October 22. Address correspondence to R.M. (e-mail: r.manniesing{at}erasmusmc.nl).

The purpose of this study was to retrospectively assess the feasibility of a fully automated image postprocessing tool for the segmentation of the arterial cerebrovasculature from computed tomographic (CT) angiography in 27 patients (nine men, 18 women; mean age, 55 years; age range, 33–76 years) with subarachnoid hemorrhage. The institutional review board approved this study, and informed consent was waived. The proposed method, which does not require the acquisition of an additional CT scan for bone suppression, consists of the following: (a) automatic detection of the main arteries for initialization, (b) segmentation of these arteries through the skull base, and (c) suppression of the large veins near the skull. The parameters of this method were optimized on the training subset of nine patients, and the method was successful at segmentation of the arteries in 15 (83%) of the 18 remaining patients. The difference between automatic and manual diameter measurements was 0.0 mm ± 0.4 (standard deviation). The study results showed that fully automated segmentation of the cerebral arteries is feasible.

Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/247/3/841/DC1

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