Hovorka R, Chappell M J, Godfrey K R, Madden F N, Rouse M K, Soons P A
Centre for Measurement and Information in Medicine, City University, London, UK.
Biopharm Drug Dispos. 1998 Jan;19(1):39-53. doi: 10.1002/(sici)1099-081x(199801)19:1<39::aid-bdd73>3.0.co;2-m.
A regularization method of deconvolution constrained to non-negative values is described. The method gives smooth estimates of the input function whilst providing a feasible fit (in terms of least squares) to measurements. A description of the program CODE (constrained deconvolution) which implements the method is given. A new methodology for a pilot evaluation of deconvolution programs is also proposed. The methodology is based on synthetic data. It employs a variety of shapes of the input function, low (1%) and high (15%) values of the measurement error, and incorporates primary (accuracy) and secondary (bias) performance measures. The performance of CODE is evaluated and it is suggested that CODE provides estimates of the input function with acceptable accuracy.
描述了一种约束为非负值的去卷积正则化方法。该方法给出输入函数的平滑估计，同时提供对测量值的可行拟合（就最小二乘法而言）。给出了实现该方法的程序CODE（约束去卷积）的描述。还提出了一种用于去卷积程序初步评估的新方法。该方法基于合成数据。它采用各种形状的输入函数、低（1%）和高（15%）的测量误差值，并纳入主要（准确性）和次要（偏差）性能指标。对CODE的性能进行了评估，结果表明CODE能以可接受的准确性提供输入函数的估计。
