title: Automatic extraction of sulcal lines on the cortical surface using shortest path probability maps.
abstract: This paper describes an automatic procedure for extracting sulcal lines from cortical surface meshes of the human brain, which will serve as a tool for landmark extraction as well as for investigating the morphometry of sulci. The procedure consists in a sequence of steps, including sulcal basin segmentation based on local curvature information, estimating a bundle of depth-constrained geodesic paths and determining a robust probability map of sulcal lines crossing. In this experiment, we present quantitative validations on two main sulci to observe the agreement of our method with manually traced curves.
authors.affiliation: Laboratoire des Sciences de l’Information et des Systèmes, UMR CNRS 6168, Marseille, France. arnaud.le-troter@univmed.fr
authors.forename: Arnaud
authors.initials: A
authors.lastname: Le Troter
authors.forename: Guillaume
authors.initials: G
authors.lastname: Auzias
authors.forename: Olivier
authors.initials: O
authors.lastname: Coulon
mesh_terms: D000465:Algorithms; D002540:Cerebral Cortex / Q000033:anatomy & histology*; D003627:Data Interpretation, Statistical; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity