Sensor Configuration Optimization in Optical Tomography: A Genetic Algorithm Approach

The sensor configuration in optical tomography systems determines the detection of the region of interest (ROI) and reconstruction performance. This work investigates the configuration optimization using a genetic algorithm (GA) to enhance reconstruction performance. The angular arrangement of emitters and receivers is combined in a vector for optimization. Parameters independent of prior target information including sensitivity uniformity, orthogonal degree (OD), and sinogram space deviation are considered in the fitness functions. To increase the number of probing beams, the beam number is also considered. Simulations are conducted to evaluate the performance of the optimized configurations compared with regular configurations. A practical tomography system is developed based on the optimal result using fan-beam lasers, and its effectiveness is verified. This optimization provides useful insights and helps improving reconstruction performance.