Paper
24 June 1998 Spiral CT of abdominal aortic aneurysms: comparison of segmentation with an automatic 3D deformable model and interactive segmentation
Andrew J. Bulpitt, Elizabeth Berry
Author Affiliations +
Abstract
A self-optimizing 3D deformable model has been developed which is able to segment branching anatomy. Its performance is compared with that of interactive segmentation in spiral CT of abdominal aortic aneurysms. SCT data from six individuals were selected retrospectively, representing a range of vascular geometry and tortuosity. As a reference, segmentation was performed twice by one observer using interactive 2D region growing. The self-optimizing 3D deformable model was applied twice, each with different initializations of the model in the aortic lumen. Dimensional and volume measurements were made, and boundary positions compared. The model was found to give qualitatively good representation, but was not able to follow vessels distal to the iliac bifurcation. The results agreed very well with the 2D interactive technique where structures ran orthogonal to the slice plane, with structures localized to 0.5 mm. The percentage difference in volume estimation between the model and the reference was 3% (the same as the agreement between the two reference segmentations). The mean closest distance between model and reference boundaries was 1.2 +/- 0.5 mm. Most discrepancies occurred at the bifurcations, and we conclude that the 3D deformable model requires further development for accurate representation of branching vascular structures in disease, but the accuracy of the model segmentation is sufficient for visualization or training.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrew J. Bulpitt and Elizabeth Berry "Spiral CT of abdominal aortic aneurysms: comparison of segmentation with an automatic 3D deformable model and interactive segmentation", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310972
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Cited by 23 scholarly publications and 4 patents.
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KEYWORDS
3D modeling

Image segmentation

Data modeling

Arteries

3D image processing

Distance measurement

Image processing

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