title: Diagnostic fidelity of the Z-buffer segmentation algorithm: preliminary assessment based on intracranial aneurysm detection.
abstract: We have developed an algorithm known as the Z-buffer segmentation (ZBS) algorithm for segmenting vascular structures from 3D MRA images. Previously we evaluated the accuracy of the ZBS algorithm on a voxel level in terms of inclusion and exclusion of vascular and background voxels. In this paper we evaluate the diagnostic fidelity of the ZBS algorithm. By diagnostic fidelity we mean that the data preserves the structural information necessary for diagnostic evaluation. This evaluation is necessary to establish the potential usefulness of the segmentation for improved image display, or whether the segmented data could form the basis of a computerized analysis tool. We assessed diagnostic fidelity by measuring how well human observers could detect aneurysms in the segmented data sets. ZBS segmentation of 30 MRA cases containing 29 aneurysms was performed. Image display used densitometric reprojections with shaded surface highlighting that were generated from the segmented data. Three neuroradiologists independently reviewed the generated ZBS images for aneurysms. The observers had 80% sensitivity (90% for aneurysms larger than 2mm) with 0.13 false positives per image. Good agreement with the gold standard for describing aneurysm size and orientation was shown. These preliminary results suggest that the segmentation has diagnostic fidelity with the original data and may be useful for improved visualization or automated analysis of the vasculature.
authors.affiliation: Department of Radiology and Center for Biomedical Informatics, University of Pittsburgh, Imaging Research, 300 Halket Street Suite 4200, Pittsburgh, PA 15213-3180, USA. bchapman@mail.magee.edu
authors.forename: Brian E
authors.initials: BE
authors.lastname: Chapman
authors.forename: Dennis L
authors.initials: DL
authors.lastname: Parker
authors.forename: Janet O
authors.initials: JO
authors.lastname: Stapelton
authors.forename: Jay S
authors.initials: JS
authors.lastname: Tsuruda
authors.forename: Claudia
authors.initials: C
authors.lastname: Mello-Thoms
authors.forename: Bronwin
authors.initials: B
authors.lastname: Hamilton
authors.forename: Gregory L
authors.initials: GL
authors.lastname: Katzman
authors.forename: Kevin
authors.initials: K
authors.lastname: Moore
mesh_terms: D000465:Algorithms; D005189:False Positive Reactions; D005240:Feasibility Studies; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D002532:Intracranial Aneurysm / Q000175:diagnosis*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D010363:Pattern Recognition, Automated; D010865:Pilot Projects; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012680:Sensitivity and Specificity