Likar B, Bernard R, Pernus F
Faculty of Electrical Engineering, University of Ljubljana, Slovenia.
Proc AMIA Annu Fall Symp. 1996:294-8.
Digital subtraction radiography (DSR) enables the detection of subtle early detrimental effects of periodontal disease as well as the evaluation of the effects of therapy. However, the differences between two radiographs due to alignment and contrast errors must be kept at minimum. In the present in vitro study we test the efficacy of three basic contrast correction methods in the reduction of contrast mismatches which can adversely affect a subtracted image. The ODTF (Optical Density Thickness Function) method, which is based on a function relating grey level values of the aluminium wedge image and the corresponding thickness of the wedge, induced less contrast correction error than the CDF (Cumulative Density Function) and the LSQA (Least Square Quadratic Approximation) methods. Moreover, CDF, ODTF, and LSQA functions obtained from the reference structure density distribution may be applied for objective contrast enhancements and for standardisation of image quality, while the ODTF function allows also bone change volume estimations.
数字减影射线照相术（DSR）能够检测牙周疾病早期的细微有害影响，并评估治疗效果。然而，由于对齐和对比度误差导致的两张射线照片之间的差异必须保持在最小程度。在本体外研究中，我们测试了三种基本对比度校正方法在减少可能对减影图像产生不利影响的对比度不匹配方面的功效。基于铝楔图像灰度值与楔相应厚度之间关系函数的ODTF（光学密度厚度函数）方法，所产生的对比度校正误差比CDF（累积密度函数）和LSQA（最小二乘二次逼近）方法要小。此外，从参考结构密度分布获得的CDF、ODTF和LSQA函数可用于客观对比度增强和图像质量标准化，而ODTF函数还可用于骨变化体积估计。
