Semiautomated segmentation of blood vessels using ellipse-overlap criteria: method and comparison to manual editing.
Two-dimensional intensity-based methods for the segmentation of blood vessels from computed-tomography-angiography data often result in spurious segments that originate from other objects whose intensity distributions overlap with those of the vessels. When segmented images include spurious segments, additional methods are required to select segments that belong to the target vessels. We describe a method that allows experts to select vessel segments from sequences of segmented images with little effort. Our method uses ellipse-overlap criteria to differentiate between segments that belong to different objects and are separated in plane but are connected in the through-plane direction. To validate our method, we used it to extract vessel regions from volumes that were segmented via analysis of isolabel-contour maps, and showed that the difference between the results of our method and manually-edited results was within inter-expert variability. Although the total editing duration for our method, which included user-interaction and computer processing, exceeded that of manual editing, the extent of user interaction required for our method was about a fifth of that required for manual editing.
Department of Radiology, Stanford University, Stanford, California 94305-5488, USA. smadar@shiffmans.net
Smadar
S
Shiffman
Geoffrey D
GD
Rubin
Pamela
P
Schraedley-Desmond
Sandy
S
Napel
D000783:Aneurysm / Q000175:diagnosis; D000792:Angiography / Q000379:methods*; D001011:Aorta / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D015588:Observer Variation; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*