Sensor Configuration Optimization in Optical Tomography: A Genetic Algorithm Approach

IF 4.3 2区综合性期刊 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Sensors Journal Pub Date : 2024-10-24 DOI:10.1109/JSEN.2024.3483264

Huajun Li;Zhihan Wei;Jiahao Dong;Wanqiang Zheng;Xiaozhao Zheng

引用次数: 0

Abstract

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.

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光学层析成像传感器配置优化：遗传算法方法

光学层析成像系统中传感器的配置决定了感兴趣区域（ROI）的检测和重建性能。本文研究了利用遗传算法优化结构以提高重构性能。将发射器和接收器的角度排列组合在一个矢量中进行优化。适应度函数中考虑了与先验目标信息无关的灵敏度均匀性、正交度（OD）和正弦图空间偏差等参数。为了增加探测光束的数量，还考虑了光束数。通过仿真比较了优化后的结构与常规结构的性能。在此基础上开发了一套实用的扇束激光层析成像系统，并对其有效性进行了验证。这种优化提供了有用的见解，并有助于提高重构性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Sensors Journal 工程技术-工程：电子与电气

CiteScore

7.70

自引率

14.00%

发文量

2058

审稿时长

5.2 months

期刊介绍： The fields of interest of the IEEE Sensors Journal are the theory, design , fabrication, manufacturing and applications of devices for sensing and transducing physical, chemical and biological phenomena, with emphasis on the electronics and physics aspect of sensors and integrated sensors-actuators. IEEE Sensors Journal deals with the following: -Sensor Phenomenology, Modelling, and Evaluation -Sensor Materials, Processing, and Fabrication -Chemical and Gas Sensors -Microfluidics and Biosensors -Optical Sensors -Physical Sensors: Temperature, Mechanical, Magnetic, and others -Acoustic and Ultrasonic Sensors -Sensor Packaging -Sensor Networks -Sensor Applications -Sensor Systems: Signals, Processing, and Interfaces -Actuators and Sensor Power Systems -Sensor Signal Processing for high precision and stability (amplification, filtering, linearization, modulation/demodulation) and under harsh conditions (EMC, radiation, humidity, temperature); energy consumption/harvesting -Sensor Data Processing (soft computing with sensor data, e.g., pattern recognition, machine learning, evolutionary computation; sensor data fusion, processing of wave e.g., electromagnetic and acoustic; and non-wave, e.g., chemical, gravity, particle, thermal, radiative and non-radiative sensor data, detection, estimation and classification based on sensor data) -Sensors in Industrial Practice