title: Estimating 3D lumen centerlines of carotid arteries in free-hand acquisition ultrasound.
abstract: OBJECTIVE
  The purpose of this paper is to present a methodology to estimate the carotid artery lumen centerlines in ultrasound (US) images obtained in a free-hand examination. Challenging aspects here are speckle noise in US images, artifacts, and the lack of contrast in the direction orthogonal to the US beam direction.
  
  
  METHODS
  An algorithm based on a rough lumen segmentation obtained by robust ellipse fitting was developed to deal with these conditions and estimate the lumen center in 2D B-mode scans. In a free-hand sweep examination, continuous image acquisitions are performed through time when the radiologist moves the probe on the patient's neck. The result is a series of images that show 2D cross-sections of the carotid's morphology. A tracking sensor (Flock of Birds) was attached to the probe and both were connected to a PC executing the Stradwin software, which relates spatial information to the acquisition data of the US probe. The spatial information was combined with the 2D lumen center estimates to provide a centerline in 3D. For validation, 19 carotid scans from 15 different patients were scanned, their centerlines calculated by the algorithm and compared with results acquired by manual annotations.
  
  
  RESULTS
  The average Euclidean distance between both among all the examinations was 0.82  mm. For each examination, the percentage of these Euclidean distances below 2  mm was calculated; the average over all examinations was 92%.
  
  
  CONCLUSIONS
  Automated 3D estimation of carotid artery lumen centerlines in free-hand real-time ultrasound is feasible and can be performed with high accuracy. The algorithm is robust enough to keep the centerlines inside the vessel, even in the absence of contrast in parts of the vessel wall.
authors.affiliation: Department of Radiology and Med. Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC, Rotterdam, The Netherlands. d.carvalho@erasmusmc.nl
authors.forename: Diego D B
authors.initials: DD
authors.lastname: Carvalho
authors.forename: Stefan
authors.initials: S
authors.lastname: Klein
authors.forename: Zeynettin
authors.initials: Z
authors.lastname: Akkus
authors.forename: Gerrit L
authors.initials: GL
authors.lastname: ten Kate
authors.forename: Arend F L
authors.initials: AF
authors.lastname: Schinkel
authors.forename: Johan G
authors.initials: JG
authors.lastname: Bosch
authors.forename: Aad
authors.initials: A
authors.lastname: van der Lugt
authors.forename: Wiro J
authors.initials: WJ
authors.lastname: Niessen
mesh_terms: D000465:Algorithms; D002339:Carotid Arteries / Q000000981:diagnostic imaging* / Q000473:pathology; D002340:Carotid Artery Diseases / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012494:Sampling Studies; D012680:Sensitivity and Specificity; D012984:Software; D018084:Ultrasonography, Interventional / Q000379:methods*