Previously reported studied to quantify articular cartilage have used labor-intensive manual or semi-automatic data-driven techniques, demonstrating high accuracy and precision. However, none has been able to automate the segmentation process. This paper describes a fast, automatic, model-based approach to segmentation and thickness measurement of the femoral cartilage in 3D T1-weighted images using active shape models (ASMs). Systematic experiments were performed to assess the accuracy and precision of the technique with in vivo images of both normal and abnormal knees. Segmentation accuracy was determined by comparing the results of the segmentation with the boundaries delineated by a radiologist. The mean error in locating the boundary was 0.57 pixels. To assess the precision of the measurement technique, the mean thickness of the femoral cartilage was calculated for repeated scans of five healthy volunteers. A mean coefficient of variation (CV) of 2.8% was obtained for the thickness measurements.
Abstract.Our objective was to test the hypothesis that focal diurnal changes occur in the femoral articular cartilage of the knee in asymptomatic young adults. Six volunteers each were scanned early in the morning, and at the end of a working day spent mainly standing. This protocol was repeated on three successive weeks. Femoral cartilage segmentations were obtained using a region-growing algorithm. These segmentations then were regridded onto a 500-pixel template, and differences in the resulting thickness maps were assessed. Analysis of variance showed no significant diurnal variation in mean thickness. There were, however, statistically-significant diurnal changes in the thickness maps. Cartilage thickness decreased during the day in three specific locations which suffer the greatest biomechanical force.
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