经MTF修正的骨X射线图象二维谱估计

Two-Dimensional Spectral Estimation of Bone X-ray Images With MTF Correction

根据骨 X射线图象的谱特征分析来决定骨质疏松的程度 ,也许可为识别个体的高骨折风险提供一种自动诊断工具 ,还可作为监控治疗有效性的客观依据 .因为各向异性骨小梁在骨 X射线图象中表现为弱纹理 ,其对二维功率谱只贡献很小一部分 ,从而导致其功率谱被成象系统的调制传递函数和噪声所遮蔽 ,这里也许可以将发现骨小梁模式的谱特征视为一种反演问题 .由于成象系统的调制传递函数和噪声可视为各向同性 ,并可统一以合成调制传递函数来表示 ,且各向同性函数在所有的角度上具有相同的投影 .因此可在重构骨 X射线图象二维功率谱的过程中 ,利用滤波反投影方法和傅立叶切片定理 ,并用合成 MTF除以投影功率谱 ,来准确地将骨小梁模式的功率谱提出 .在骨 X射线图象和合成图象上进行的实验结果表明 ,由于各向异性的骨小梁 ,在重构的二维功率谱中有差异显著的峰 ,因此一旦获得骨小梁的功率谱 ,就可定位最大峰值频率 ,以用于估计骨小梁间距和角度 ,以及其他纹理特征 ,进而用来描述其各向异性的程度 .由于这些纹理特征与骨结构直接相关 ,因此可用于预测骨折风险 .

Determination of degree of osteoporosis from spectrum feature analysis of bone radiographs will provide a screening tool to identify individuals with high fracture risks, and also an objective way to monitor treatment effectiveness reliably. This article shows that since the anisotropic trabecular appear weakly in bone X-ray images and contribute a small portion to the power spectrum, and cause that the signal(trabecular) power spectrum is masked by the noise and the MTF(modulation transfer function) of the imaging system, finding spectral characteristics of trabecular patterns may be considered as an inverse problem. It is assumed that the MTF of the imaging system and the noise introduced by film digitizer are isotropic. The isotropic parts are summarized as the synthetic MTF. An isotropic function have the same projection across all angles. The power spectrum of trabecular patterns can be approximated by reconstructing the 2-D power spectrum from the projection power spectra divided by the synthetic MTF based on Filtered Backprojection Algorithm and Fourier Slice Theorem. Experiments on the bone X-ray images and the synthetic images demonstrate that the anisotropic trabecular pattern have distinguished peaks in the reconstructed power spectrum. Once the signal power spectrum is obtained, it is staightfoward to find maximum peak to estimate the trabecular spacing and the trabecular angle and other texture features to describe the degree of anisotropy. These features are directly related to bone structure, therefore, can be used to produce a summary index to predict the fracture risk.