title: A method for morphological characterization of dural ectasia in Marfan syndrome.
abstract: In this paper we reported a novel method to detect and quantify dural ectasia in Marfan syndrome. Firstly, the dural sacs of 8 Marfan patients were segmented by applying an unsupervised Fuzzy C-Means method on T2-weighed magnetic resonance images. Then, for each patient a tubular model of the dural sac was extracted by detecting and removing the existent pathological extrusions. The segmented images together with the resulting tube were then rendered using a marching cubes algorithm. The proposed algorithm represents a first attempt to quantify and to morphologically characterize the pathological ectasia that usually accompanies the Marfan disorder. The generated 3D reconstruction and the opportunity to overlap them with a physiological model provides the clinician with a tool for a panoramic view of the structures and a means for a more accurate inspection of ectasia. In addition the extracted parameters furnish quantitative and reproducible measures that could be useful as discriminative indexes for an automatic and more objective diagnosis.
authors: Biomedical Engineering Department, Politecnico di Milano, Milan, Italy. maria.iacono@mail.polimi.it
authors: Maria I
authors: MI
authors: Iacono
authors: Katia
authors: K
authors: Passera
authors: Lorenzo
authors: L
authors: Magrassi
authors: Roberto
authors: R
authors: Dore
authors: Paolo
authors: P
authors: Lago
authors: Eloisa
authors: E
authors: Arbustini
authors: Luca T
authors: LT
authors: Mainardi
mesh_terms: D000465:Algorithms; D004108:Dilatation, Pathologic / Q000473:pathology; D004388:Dura Mater / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008382:Marfan Syndrome / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity