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Proceedings Paper

An automated system for the analysis of peri-prosthetic osteolysis progression
Author(s): Jose Tamez-Pena; Monica Barbu-McInnis; S. Kubilay Pakin; Benjamin Castaneda; Saara Totterman; R. John Looney
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Paper Abstract

The purpose of this work is to evaluate the performance of a computer based analysis system aimed at the quantitative detection of changes in hip osteolytic lesions in subjects with hip implants. The computer system is based on the supervised segmentation of a baseline x-ray computed-tomography (CT) scan and an automated segmentation of a follow-up CT scan using an object based tracking algorithm. The segmentation process outlines the pelvic bone and lesions present in the pelvis. The size and CT density of the osteolytic lesions are computed in both baseline and follow-up segmentations and the change in both these quantities are evaluated. The system analysis consisted of the direct comparison of the quantitative results obtained from an expert manual segmentation to the quantitative results obtained using the automated system on 20 subjects. The system bias was evaluated by performing forwards and backwards analysis of the CT data. Furthermore, the stability of the proposed tracking system was compared to the variability of the manual tracking. The results show that the system enhances the human ability to detect changes in lesions size and density regardless of the inherent observer variability in the definition of the baseline manual segmentation.

Paper Details

Date Published: 6 March 2008
PDF: 9 pages
Proc. SPIE 6917, Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment, 691718 (6 March 2008); doi: 10.1117/12.770715
Show Author Affiliations
Jose Tamez-Pena, VirtualScopics, Inc. (United States)
Monica Barbu-McInnis, VirtualScopics, Inc. (United States)
S. Kubilay Pakin, VirtualScopics, Inc. (United States)
Benjamin Castaneda, Univ. of Rochester (United States)
Saara Totterman, VirtualScopics, Inc. (United States)
R. John Looney, Univ. of Rochester, School of Medicine (United States)

Published in SPIE Proceedings Vol. 6917:
Medical Imaging 2008: Image Perception, Observer Performance, and Technology Assessment
Berkman Sahiner; David J. Manning, Editor(s)

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