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Predicting Osteoporosis by Analyzing Fracture Risk Factors and Trabecular Microarchitectures of the Proximal Femur from DXA Images

机译:通过分析来自DXA图像的骨折危险因素和近端股骨的小梁微体系结构来预测骨质疏松症

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This study aimed to identify the optimal threshold ranges for predicting osteoporosis and osteoporotic fractures by analyzing the correlations between trabecular patterns and fracture risk factors. We selected 85 post-menopausal women as experimental subjects and classified them into 29 normal and 56 osteoporotic groups. We proposed a novel thresholding algorithm that divides the threshold ranges from 0 to 95% based on trabecular bone area and assessed osteoporosis predictability for each range. Evaluation parameters were categorized into morphological parameters (Tb.Area, Sk.Length and fractal dimension) and fracture risk factors (MSCT, LSCT, FNW, TW, FNAL and HAL). Consequently, we found the clinical usefulness of our algorithm for discriminating patients with osteoporosis from those with normal bone. The significances between the morphological parameters and the fracture risk factors improved as bone mineral density decreased. Based on these results, we selected the optimal threshold conditions for predicting osteoporosis and osteoporotic fractures at thresholds of 40-80%.
机译:本研究旨在通过分析小梁图案与骨折危险因素之间的相关性来识别用于预测骨质疏松症和骨质疏松骨折的最佳阈值范围。我们选择了85名绝经后妇女作为实验性受试者,并将它们分为29个正常和56个骨质疏松群体。我们提出了一种新的阈值算法,其基于小梁骨面积将阈值分成0〜95%,并评估每个范围的骨质疏松症可预测性。评估参数分为形态参数(TB.AREA,SK.Length和分形尺寸)和断裂危险因素(MSCT,LSCT,FNW,TW,FNAL和HAL)。因此,我们发现了我们算法的临床有用性,以鉴定患有正常骨骼的骨质疏松症的患者。形态学参数与骨折危险因素之间的重要性改善为骨矿物质密度降低。基于这些结果,我们选择了以40-80%的阈值预测骨质疏松症和骨质疏松骨折的最佳阈值条件。

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