ISSN 1004-4140
CN 11-3017/P
Volume 31 Issue 6
Nov.  2022
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Abstract
References
SUN L, BAI J, DI W Q, et al. Research on blood flow separation algorithm of diffuse light correlation spectrum based on ICA[J]. CT Theory and Applications, 2022, 31(6): 809-820. DOI: 10.15953/j.ctta.2022.132. (in Chinese).
Citation: SUN L, BAI J, DI W Q, et al. Research on blood flow separation algorithm of diffuse light correlation spectrum based on ICA[J]. CT Theory and Applications, 2022, 31(6): 809-820. DOI: 10.15953/j.ctta.2022.132. (in Chinese).
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Research on Blood Flow Separation Algorithm of Diffuse Light Correlation Spectrum Based on ICA

  • School of Information and Communication Engineering, North University of China, Taiyuan 030051, China

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  • Received Date: July 04, 2022
  • Revised Date: August 06, 2022
  • Accepted Date: August 06, 2022
  • Available Online: August 21, 2022
  • Published Date: November 02, 2022
    Graphical Abstract
    • Abstract
  • 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.
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    • References (36)
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