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Improvement of the Frequency-domain Inverse Monte Carlo Simulation

Author: ZhouXiaoQing
Tutor: ZhaoHuiJuan
School: Tianjin University
Course: Biomedical Engineering
Keywords: Near-infrared diffuse light Frequency domain Inverse Monte Carlo simulation Cluster analysis
CLC: R737.33
Type: Master's thesis
Year: 2010
Downloads: 31
Quote: 0
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The near-infrared diffuse light measurement of the frequency domain is a new technology to achieve early diagnosis of cervical cancer . Near infrared diagnostic method using detection of 600-900nm light source , the non-invasive diagnosis of physiological information . Until now , the typical frequency domain system or endoscopic detection of early cervical lesions near-infrared system . Taking into account the special shape of the cervical tissue and its large range of optical parameters , the Monte Carlo model (Monte Carlo, MC) is selected as the propagation of light in a organization forward model . In this paper, the optical parameters of the cervical tissue ( absorption coefficient μ_a the scattering coefficient μ_s) reconstructed the issues . Improve the efficiency and accuracy of the inverse Monte Carlo reconstruction technique . Frequency-domain information database , through the establishment of certain optical parameters within the forward MC simulation and surface fitting bivariate polynomial regression method known frequency-domain information , quick access to any iteration of the inverse problem of optical parameters in the frequency domain . In the inverse problem , the application of LM optimization algorithm reconstructed optical parameters by analyzing the relationship of initial value selection and Reconstruction results , the introduction of a clustering method to determine its iterative initial value , to overcome the local LM algorithm optimization features . And analog validation and experimental validation . Simulation and verification results show that , using this inverse Monte Carlo reconstruction technique in cervical tissue optical parameters within the relative refactoring of μ_a error is less than 2 % relative μ_s reconstruction error of less than 5% , and reconstruction of a set of optical parameters in less than 0.5 seconds. Finally, the use of the three phantoms endoscopic measurement experiments further verify the feasibility of the algorithm .

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