基于样本的参数化方法在电阻抗成像中的应用
On Reconstruction of Binary Images by Efficient Sample-based Parameterization in Applications for Electrical Impedance Tomography
摘要：
一个有效的计算方法，适合在各种应用，包括生物医学成像模型的二进制类型的图像的最佳重建开发和验证。该方法包括衍生物的自由优化支持的一组样品的解决方案与定制的几何合成生成。降维控制空间是基于来自各个样本的贡献和从样本几何形状的描述获得的有效参数化来组织的。整个框架具有易于遵循的设计，由于标称数量的调整参数，这使得该方法在各种设置中的实际实施变得简单，并且可以将其调整为新模型并提高性能。通过应用坐标下降法以预定义的自定义顺序处理各个控件，可以实现计算时间的高效率。这种技术被证明优于常用的基于梯度和其他衍生物的方法与应用PCA为基础的控制空间减少的二进制图像的质量和稳定性的解决方案时，噪声存在于测量数据。完整的计算框架的性能进行了测试，在应用程序中的二维逆问题检测夹杂物或缺陷区域的电阻抗断层成像（EIT）。结果表明，新方法的有效性能和其高潜力，提高整体质量的EIT为基础的程序，包括生物医学应用。
英文摘要：
An efficient computational approach for optimal reconstruction of binary-type images suitable for models in various applications including biomedical imaging is developed and validated. The methodology includes derivative-free optimization supported by a set of sample solutions with customized geometry generated synthetically. The reduced dimensional control space is organized based on contributions from individual samples and the efficient parameterization obtained from the description of the samples' geometry. The entire framework has an easy-to-follow design due to a nominal number of tuning parameters which makes the approach simple for practical implementation in various settings, as well as for adjusting it to new models and enhancing the performance. High efficiency in computational time is achieved through applying the coordinate descent method to work with individual controls in the predefined custom order. This technique is shown to outperform commonly used gradient-based and other derivative-free methods with applied PCA-based control space reduction in terms of both qualities of binary images and stability of obtained solutions when noise is present in the measurement data. The performance of the complete computational framework is tested in applications to 2D inverse problems of detecting inclusions or defective regions by the electrical impedance tomography (EIT). The results demonstrate the efficient performance of the new method and its high potential for improving the overall quality of the EIT-based procedures including biomedical applications.
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