title: Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.
abstract: Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure.
authors.affiliation: Department of Telecommunications and Information Processing/TELIN-IPI-IBBT, Faculty of Engineering, Ghent University, Sint-Pietersnieuwstraat 41, 0 Ghent, Belgium. dbabin@telin.ugent.be
authors.forename: D
authors.initials: D
authors.lastname: Babin
authors.forename: A
authors.initials: A
authors.lastname: Pižurica
authors.forename: R
authors.initials: R
authors.lastname: Bellens
authors.forename: J
authors.initials: J
authors.lastname: De Bock
authors.forename: Y
authors.initials: Y
authors.lastname: Shang
authors.forename: B
authors.initials: B
authors.lastname: Goossens
authors.forename: E
authors.initials: E
authors.lastname: Vansteenkiste
authors.forename: W
authors.initials: W
authors.lastname: Philips
mesh_terms: D000465:Algorithms; D002533:Cerebral Angiography / Q000379:methods*; D006801:Humans; D002538:Intracranial Arteriovenous Malformations / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*