Buie Helen R, Campbell Graeme M, Klinck R Joshua, MacNeil Joshua A, Boyd Steven K
Department of Mechanical and Manufacturing Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive N.W., Calgary, Alberta, Canada T2N 1N4.
Bone. 2007 Oct;41(4):505-15. doi: 10.1016/j.bone.2007.07.007. Epub 2007 Jul 18.
The use of high resolution peripheral quantitative computed tomography (HR-pQCT) and in vivo micro-CT for studies of bone disease and treatment has become increasingly common, and with these methods comes large quantities of data requiring analysis. A simple, robust, and fully-automated segmentation algorithm is presented that efficiently segments bone regions. The dual threshold technique refers to two required threshold inputs that are used to extract the periosteal and endosteal surfaces of the cortex. The proposed method was tested against the gold standard, semi-automated hand contouring, using 45 datasets: mouse, rat, human, and cadaver data from the tibia or radius with nominal isotropic resolutions of 10-82 microm. The performance of the proposed method to segment cortical and trabecular compartments was evaluated qualitatively from visualizations and quantitatively based on morphological measurements. Visual inspection confirmed successful segmentation of all datasets using the new method, with qualitatively better results when applied to the human and cadaver data compared to the gold standard. The dual threshold algorithm was able to extract thin and porous cortices, whereas some clipping and perforations occurred for the gold standard. Morphological parameters measured for segmentation by the proposed method versus the gold standard agreed (95% confidence) for Tb.Th, Tb.Sp, and Tb.N, but not Ct.Th and BV/TV for the human and cadaver datasets. Nonetheless, correlations ranged from 0.95 to 1.00 for all morphological parameters except the cadaver Ct.Th because systematic errors were present. Poor agreement for Ct.Th and BV/TV was due to qualitatively incorrect segmentation by the gold standard when the cortex was thin compared to trabeculae, or operator bias during hand contouring. Since Tb.Th, Tb.Sp, and Tb.N were insensitive to segmentation method, despite operator bias, they are robust parameters for inter-site comparisons. The dual threshold method offers a robust and fully-automated alternative to the gold standard that can efficiently segment bone regions with accurate and repeatable results. The algorithm can be easily implemented since it uses simple image analysis tools. Two input thresholds allow adjustment of the masked output, and are easily determined by trial and error. Using the same input thresholds for similar datasets assures maximal consistency while alleviating time consuming semi-automated contouring.
使用高分辨率外周定量计算机断层扫描（HR-pQCT）和体内微型CT来研究骨疾病及治疗方法已变得越来越普遍，随之而来的是大量需要分析的数据。本文提出了一种简单、稳健且完全自动化的分割算法，可有效地分割骨区域。双阈值技术指的是两个所需的阈值输入，用于提取皮质的骨膜和骨内膜表面。使用45个数据集（来自小鼠、大鼠、人类以及胫骨或桡骨的尸体数据，标称各向同性分辨率为10 - 82微米），将所提出的方法与金标准（半自动手动轮廓描绘）进行了对比测试。从可视化角度定性评估了所提出方法对皮质和小梁部分进行分割的性能，并基于形态学测量进行了定量评估。目视检查证实使用新方法成功分割了所有数据集，与金标准相比，应用于人类和尸体数据时定性结果更好。双阈值算法能够提取薄且多孔的皮质，而金标准则出现了一些裁剪和穿孔情况。所提出方法与金标准分割测量得到的形态学参数在Tb.Th、Tb.Sp和Tb.N方面（95%置信度）相符，但在人类和尸体数据集中，Ct.Th和BV/TV不相符。尽管如此，除尸体Ct.Th外，所有形态学参数的相关性范围为0.95至1.00，因为存在系统误差。Ct.Th和BV/TV一致性较差是由于当皮质比小梁薄时金标准的定性分割不正确，或者是手动轮廓描绘过程中的操作者偏差。由于Tb.Th、Tb.Sp和Tb.N对分割方法不敏感，尽管存在操作者偏差，但它们是用于不同部位比较的稳健参数。双阈值方法为金标准提供了一种稳健且完全自动化的替代方案，能够以准确且可重复的结果有效地分割骨区域。该算法使用简单的图像分析工具，易于实现。两个输入阈值允许调整掩码输出，并且通过试错法很容易确定。对相似数据集使用相同的输入阈值可确保最大程度的一致性，同时避免耗时的半自动轮廓描绘。
