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The use of active shape models for making thickness measurements of articular cartilage from MR images

机译:使用活动形状模型从mR图像进行关节软骨的厚度测量

摘要

Previously reported studies 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 e 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.
机译:先前报道的量化关节软骨的研究使用了劳动密集型的手动或半自动数据驱动技术,证明了其高精度和高精度。但是,没有人能够自动执行分割过程。本文介绍了一种基于模型的快速,自动,基于模型的方法,该方法使用活动形状模型(ASM)对3D T1加权图像中的股骨软骨进行分割和厚度测量。进行了系统性实验,以通过正常和异常膝盖的体内图像评估该技术的准确性和精确性。通过将分割结果与放射线医师划定的边界进行比较,确定分割精度。定位边界的平均误差为0.57像素。为了评估测量技术的准确性,计算了五名健康志愿者的股骨软骨平均厚度。厚度测量的平均变异系数(CV)为2.8%。

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