title: Prior-based automatic segmentation of the carotid artery lumen in TOF MRA (PASCAL).
abstract: In current clinical practice, examinations of the carotid artery bifurcation are commonly carried out with Computed Tomography Angiography (CTA) or contrast-enhanced Magnetic Resonance Angiography (ceMRA). Quantitative information about vessel morphology, extracted from segmentations, is promising for diagnosis of vessel pathologies. However, both above-mentioned techniques require the administration of contrast media. In contrary, non-ceMRA methods such as Time-of-Flight (TOF) provide fully non-invasive imaging without any exogenous contrast agent. The diagnostic value of TOF MRA, however, for assessment of the carotid bifurcation area can be hampered due to its susceptibility to irregular blood flow patterns. Conventional methods for lumen segmentation are very sensitive to such signal voids and produce inaccurate results. In this work, a novel, fully automatic 3D segmentation algorithm is proposed which uses prior knowledge about irregular flow patterns. The presented technique has been successfully tested on eleven volunteer datasets as well as in a patient case, offering the comparison to CTA images. The sensitivity could be increased by 29.2% to 85.6% compared to standard level set methods. The root mean squared error in diameter measurements was reduced from 4.85 mm to 1.44 mm.
authors.affiliation: Pattern Recognition Lab, University Erlangen-Nuremberg, Germany.
authors.forename: Jana
authors.initials: J
authors.lastname: Hutter
authors.forename: Hannes G
authors.initials: HG
authors.lastname: Hofmann
authors.forename: Robert
authors.initials: R
authors.lastname: Grimm
authors.forename: Andreas
authors.initials: A
authors.lastname: Greiser
authors.forename: Marc
authors.initials: M
authors.lastname: Saake
authors.forename: Joachim
authors.initials: J
authors.lastname: Hornegger
authors.forename: Arnd
authors.initials: A
authors.lastname: Dörfler
authors.forename: Peter
authors.initials: P
authors.lastname: Schmitt
mesh_terms: D000465:Algorithms; D002339:Carotid Arteries / Q000473:pathology*; D016893:Carotid Stenosis / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique