RATIONALE AND OBJECTIVES: This article presents an evaluation of an automated technique for determining the colon centerline with computed tomographic (CT) data sets. MATERIALS AND METHODS: The technique proceeds as follows. After indication of a voxel in the rectum, voxels corresponding to air were segmented. Points along the colon centerline were estimated on the basis of centers of mass of grown voxels. A second segmentation and centerline calculation was initiated at the cecum. These two centerlines were then averaged. The resulting average was refined by using lumen data obtained perpendicular to the average centerline. The accuracy of the technique was investigated with simulation phantoms. The technique was also evaluated for 40 clinical colon cases. Calculated centerline points were compared with those indicated by radiologists for a randomly selected clinical case. RESULTS: In the simulation studies, the calculated centerline points were, on average, within 2.5 mm of the true centerlines but differed by up to 4 mm in regions of deep folds or sharp turns. In the clinical colon study, 40% of the centerlines were computed with a single seed point and 25% with two seed points. Average centerlines were computed in 1 minute. The root mean square difference between the computed centerline points and those indicated by the radiologists was 4-5 mm (comparable to interobserver variations). CONCLUSION: Accurate centerlines can be determined from colon CT data with this automated technique.
RATIONALE AND OBJECTIVES: This article presents an evaluation of an automated technique for determining the colon centerline with computed tomographic (CT) data sets. MATERIALS AND METHODS: The technique proceeds as follows. After indication of a voxel in the rectum, voxels corresponding to air were segmented. Points along the colon centerline were estimated on the basis of centers of mass of grown voxels. A second segmentation and centerline calculation was initiated at the cecum. These two centerlines were then averaged. The resulting average was refined by using lumen data obtained perpendicular to the average centerline. The accuracy of the technique was investigated with simulation phantoms. The technique was also evaluated for 40 clinical colon cases. Calculated centerline points were compared with those indicated by radiologists for a randomly selected clinical case. RESULTS: In the simulation studies, the calculated centerline points were, on average, within 2.5 mm of the true centerlines but differed by up to 4 mm in regions of deep folds or sharp turns. In the clinical colon study, 40% of the centerlines were computed with a single seed point and 25% with two seed points. Average centerlines were computed in 1 minute. The root mean square difference between the computed centerline points and those indicated by the radiologists was 4-5 mm (comparable to interobserver variations). CONCLUSION: Accurate centerlines can be determined from colon CT data with this automated technique.
Authors: Sebastian Schafer; Vikas Singh; Peter B Noël; Alan M Walczak; Jinhui Xu; Kenneth R Hoffmann Journal: Int J Comput Assist Radiol Surg Date: 2009-07-18 Impact factor: 2.924
Authors: Jeff Goldsmith; Brian Caffo; Ciprian Crainiceanu; Daniel Reich; Yong Du; Craig Hendrix Journal: Ann Appl Stat Date: 2011-01-01 Impact factor: 2.083