OPTIMIZATION OF DATA ACQUISITION IN OPTICAL TOMOGRAPHY BASED ON ESTIMATION THEORY

In any experimental platform, data acquisition is the first and essential step, and occasionally the most time-consuming and costly operation. During the process of data acquisition, we conduct experiments to measure the response of the system to a set of inputs. Methods of optimal design of experiment can be used to determine the most informative measurements and avoid numerous traps that trial-and-error experimentation might cause. In this research, we have developed a general approach for designing optimal experiments, subsequently applying it to the domain of optical tomography.
Optical tomography is a vital technology that enables three-dimensional imaging by reconstructing images from two-dimensional projections. This technology has applications across various fields, including medicine and material science. The process involves two main phases: data acquisition and image reconstruction. The traditional raster scanning method has been the standard approach for data acquisition, but it presents challenges in terms of scanning speed, quality, and exposure to harmful radiations in some cases. This has prompted researchers to explore ways to optimize the scanning process.