Acta Optica Sinica, Volume. 43, Issue 3, 0311001(2023)
Configuration Optimization of Optical Tomography Based on Genetic Algorithm
Fig. 2. Regular configuration with 25 emitters and 25 receivers. (a) Structure of sensor; (b) schematic diagram of beam distribution; (c) sensitivity map; (d) angular location distribution
Fig. 5. Optimization results of genetic algorithm. (a) Iteration process of genetic algorithm; (b) schematic diagram of sensor arrangement of optimized configuration
Fig. 6. Beam distribution map and sensitivity map. (a)-(c) Beam distribution map; (d)-(f) sensitivity map
Fig. 7. Specific distributions of five structures. (a) Single phantom with "hard-edge"; (b) double phantoms with "hard-edge"; (c) Gaussian phantom with "soft-edge"; (d) cross structure with "hard-edge"; (e) concave structure with "hard-edge"
Fig. 8. Reconstruction results of three configurations. (a)(d)(g)(j)(m) Random configuration; (b)(e)(h)(k)(n) regular configuration; (c)(f)(i)(l)(o) optimized configuration
Fig. 9. Local reconstruction error at central axis of random configuration, regular configuration and optimized configuration. (a) Random configuration; (b) regular configuration; (c) optimized configuration
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Xiaozhao Zheng, Jiyang Yao, Huajun Li, Shanen Yu. Configuration Optimization of Optical Tomography Based on Genetic Algorithm[J]. Acta Optica Sinica, 2023, 43(3): 0311001
Category: Imaging Systems
Received: Jun. 2, 2022
Accepted: Aug. 9, 2022
Published Online: Feb. 13, 2023
The Author Email: Li Huajun (hjli@hdu.edu.cn)