Application of Reconstruction and Optimization Algorithms in Optical Tomography

U. Hashmi, Raheel Muzzammel, R. Arshad, Saba Mehmood
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引用次数: 1

Abstract

Optical tomography is a non-invasive technique that uses visible or near infrared radiation to analyze biological tissues. Researchers take immense attention towards advancement in optical tomography because of its low cost and an advantage of providing anatomical information. Based on the information of optical characteristics, forward and inverse problem of tomography are solved. In this research, finite element method is employed for forward problem and gradient-based optimization algorithm is developed for inverse problem of optical tomography. It is found from simulations that information about imaging is processed more distinctly and in less computational time. Normal and abnormal conditions in imaging are readily distinguished. Simulations are carried out in Matlab. Different scenarios are developed and are simulated to validate the performance of reconstruction and optimization algorithms in optical tomography.
重建与优化算法在光学层析成像中的应用
光学断层扫描是一种使用可见光或近红外辐射来分析生物组织的非侵入性技术。光学层析成像技术以其低成本和提供解剖学信息的优势而备受关注。基于光学特性信息,解决了层析成像的正反问题。本研究采用有限元法求解光学层析成像的正问题,采用梯度优化算法求解光学层析成像的反问题。仿真结果表明,图像信息处理更加清晰,计算时间更短。影像上的正常和异常情况很容易区分。在Matlab中进行了仿真。开发并模拟了不同的场景,以验证光学层析成像中重建和优化算法的性能。
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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