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Local Binary Patterns to Evaluate Trabecular Bone Structure from Micro-CT Data: Application to Studies of Human Osteoarthritis

机译:局部二进制模式以评估微型CT数据的小梁骨结构:应用于人骨关节炎的研究

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Osteoarthritis (OA) causes progressive degeneration of articular cartilage and pathological changes in subchondral bone. These changes can be assessed volumetrically using micro-computed tomography (μCT) imaging. The local descriptor, i.e. local binary pattern (LBP), is a new alternative solution to perform analysis of local bone structures from μCT scans. In this study, different trabecular bone samples were prepared from patients diagnosed with OA and treated with total knee arthroplasty. The LBP descriptor was applied to correlate the distribution of local patterns with the severity of the disease. The results obtained suggest the appearance and disappearance of specific oriented patterns with OA, as an adaptation of the bone to the decrease of cartilage thickness. The experimental results suggest that the LBP descriptor can be used to assess the changes in the trabecular bone due to OA.
机译:骨关节炎(OA)导致骨髓内骨的关节软骨和病理变化的进步变性。可以使用微计算机断层扫描(μCT)成像在体内评估这些变化。本地描述符,即本地二进制模式(LBP)是一种新的替代解决方案,以便从μCT扫描进行局部骨结构的分析。在这项研究中,由诊断为OA的患者制备不同的小梁骨样品,并用全膝关节置换术治疗。应用LBP描述符以将局部模式的分布与疾病的严重程度相关联。所获得的结果表明,特定定向图案的外观和消失与OA,作为骨骼的调整,以使软骨厚度降低。实验结果表明,LBP描述符可用于评估由于OA引起的小梁骨的变化。

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