Bone texture characterization for osteoporosis diagnosis using digital radiography.
Bone texture characterization for osteoporosis diagnosis using digital radiography.
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DOI：
10.1109/embc.2016.7590879
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发表时间：
2016-08
期刊：
影响因子：
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通讯作者：
Makrogiannis S
中科院分区：
文献类型：
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作者：
Keni Zheng;Makrogiannis S
我们引入纹理分类技术，以有效地诊断骨质疏松症的骨摄影数据。骨质疏松症是一种与年龄相关的全身性骨骨骼疾病，其特征是低骨量和骨结构退化，导致骨脆性增加和骨折风险增加。因此，早期诊断可以有效预测骨折风险，预防疾病。从数字X光照片进行自动诊断是非常具有挑战性的，因为健康受试者和乳腺癌受试者的扫描显示很少或没有视觉差异，并且它们的密度直方图大多重叠。我们设计了一个系统，以区分健康的，使用从射线照片计算的高维纹理特征表示。这些特征，然后减少使用特征选择，以获得更多的判别子集，最终分类我们的方法。在116张骨X光片上，表现最好的方法产生了79.3%的准确性和81%的ROC下面积。
We introduce texture classification techniques to effectively diagnose osteoporosis in bone radiography data. Osteoporosis is an age-related systemic bone skeletal disorder characterized by low bone mass and bone structure deterioriation that results in increased bone fragility and higher fracture risk. Therefore, early diagnosis can effectively predict fracture risk and prevent the disease. Automated diagnosis from digital radiographs is very challenging since the scans of healthy and osteoporotic subjects show little or no visual differences, and their density histograms mostly overlap. We designed a system to separate healthy from osteoporotic subjects using high-dimensional textural feature representations computed from radiographs. These features were then reduced using feature selection to obtain the more discriminant subset that was finally classified by our methods. The top performing approach yields 79.3% accuracy and 81% area under the ROC over 116 bone radiographs.