The data acquisition process is occasionally the most time consuming and costly operation in tomography. Currently, raster scanning is still the common practice in making sequential measurements in most tomography scanners. Raster scanning is known to be slow and such scanners usually cannot catch up with the speed of changes when imaging dynamically evolving objects. In this research, we studied the possibility of using estimation theory and our prior knowledge about the sample under test to reduce the number of measurements required to achieve a given image quality. This systematic approach for optimization of the data acquisition process also provides a vision toward improving the geometry of the scanner and reducing the effect of noise, including the common state-dependent noise of detectors. The theory is developed in the article and simulations are provided to better display discussed concepts.

中文翻译：

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基于估计理论的光学层析成像数据采集操作优化

数据采集​​过程有时是断层扫描中最耗时和最昂贵的操作。目前，光栅扫描仍然是大多数断层扫描仪进行顺序测量的常见做法。众所周知，光栅扫描速度很慢，并且此类扫描仪在对动态演变的对象进行成像时通常无法赶上变化的速度。在这项研究中，我们研究了使用估计理论和我们对被测样本的先验知识来减少实现给定图像质量所需的测量次数的可能性。这种优化数据采集过程的系统方法还提供了改善扫描仪几何形状和减少噪声影响的愿景，包括探测器的常见状态相关噪声。