Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA
Blood flow is an important physiological parameter of the human body. Real-time measurement of blood flow in the brain, skeletal muscle, and breast tissue is of great significance for disease diagnosis, treatment, surgery, and intensive care. Near-Infrared Diffuse Correlation Spectroscopy (DCS) is a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Editorial Office of Computerized Tomography Theory and Application
2022-12-01
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| Series: | CT Lilun yu yingyong yanjiu |
| Subjects: | |
| Online Access: | https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2022.132 |
| _version_ | 1797776498636095488 |
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| author | Ling SUN Jing BAI Wenqi DI Yu SHANG |
| author_facet | Ling SUN Jing BAI Wenqi DI Yu SHANG |
| author_sort | Ling SUN |
| collection | DOAJ |
| description | Blood flow is an important physiological parameter of the human body. Real-time measurement of blood flow in the brain, skeletal muscle, and breast tissue is of great significance for disease diagnosis, treatment, surgery, and intensive care. Near-Infrared Diffuse Correlation Spectroscopy (DCS) is a new-type tissue blood flow measurement technology. When using DCS technology for blood flow measurement, the light source-detector (S-D) at each distance contains different degrees of mixed signals of superficial and deep tissues, among which the superficial signals show greater impact on the extraction of blood flow in deep tissues. This paper combines the Nth order linear algorithm (NL algorithm) with the independent component analysis algorithm (Independent Component Analysis, ICA) to separate and process the short-range and long-range optical signals obtained by DCS technology. The computer simulation shows that the algorithm proposed in this paper can better separate the blood flow signals of the superficial and deep tissues, and demonstrates important potential for the application of DCS technology in clinical blood flow measurement in the future. |
| first_indexed | 2024-03-12T22:50:51Z |
| format | Article |
| id | doaj.art-3958b4449c774185b22bd51c5a23ce80 |
| institution | Directory Open Access Journal |
| issn | 1004-4140 |
| language | English |
| last_indexed | 2024-03-12T22:50:51Z |
| publishDate | 2022-12-01 |
| publisher | Editorial Office of Computerized Tomography Theory and Application |
| record_format | Article |
| series | CT Lilun yu yingyong yanjiu |
| spelling | doaj.art-3958b4449c774185b22bd51c5a23ce802023-07-20T08:59:34ZengEditorial Office of Computerized Tomography Theory and ApplicationCT Lilun yu yingyong yanjiu1004-41402022-12-0131680982010.15953/j.ctta.2022.1322022.132Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICALing SUN0Jing BAI1Wenqi DI2Yu SHANG3School of Information and Communication Engineering, North University of China, Taiyuan 030051, ChinaSchool of Information and Communication Engineering, North University of China, Taiyuan 030051, ChinaSchool of Information and Communication Engineering, North University of China, Taiyuan 030051, ChinaSchool of Information and Communication Engineering, North University of China, Taiyuan 030051, ChinaBlood flow is an important physiological parameter of the human body. Real-time measurement of blood flow in the brain, skeletal muscle, and breast tissue is of great significance for disease diagnosis, treatment, surgery, and intensive care. Near-Infrared Diffuse Correlation Spectroscopy (DCS) is a new-type tissue blood flow measurement technology. When using DCS technology for blood flow measurement, the light source-detector (S-D) at each distance contains different degrees of mixed signals of superficial and deep tissues, among which the superficial signals show greater impact on the extraction of blood flow in deep tissues. This paper combines the Nth order linear algorithm (NL algorithm) with the independent component analysis algorithm (Independent Component Analysis, ICA) to separate and process the short-range and long-range optical signals obtained by DCS technology. The computer simulation shows that the algorithm proposed in this paper can better separate the blood flow signals of the superficial and deep tissues, and demonstrates important potential for the application of DCS technology in clinical blood flow measurement in the future.https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2022.132diffuse light correlation spectrumn-order linear algorithmindependent component analysisblood flow |
| spellingShingle | Ling SUN Jing BAI Wenqi DI Yu SHANG Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA CT Lilun yu yingyong yanjiu diffuse light correlation spectrum n-order linear algorithm independent component analysis blood flow |
| title | Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA |
| title_full | Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA |
| title_fullStr | Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA |
| title_full_unstemmed | Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA |
| title_short | Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA |
| title_sort | research on blood flow separation algorithm of diffuse light correlation spectrum based on ica |
| topic | diffuse light correlation spectrum n-order linear algorithm independent component analysis blood flow |
| url | https://www.cttacn.org.cn/cn/article/doi/10.15953/j.ctta.2022.132 |
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