Near-Infrared Forearm Vascular Width Calculation Using Radius Estimation of Tangent Circle

Qianru Ji, Haoting Liu* (Corresponding Author), Zhen Tian, Song Wang* (Corresponding Author), Qing Li, Dewei Yi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

In response to the analysis of the functional status of forearm blood vessels, this paper fully considers the orientation of the vascular skeleton and the geometric characteristics of blood vessels and proposes a blood vessel width calculation algorithm based on the radius estimation of the tangent circle (RETC) in forearm near-infrared images. First, the initial infrared image obtained by the infrared camera is preprocessed by image cropping, contrast stretching, denoising, enhancement, and initial segmentation. Second, the Zhang–Suen refinement algorithm is used to extract the vascular skeleton. Third, the Canny edge detection method is used to perform vascular edge detection. Finally, a RETC algorithm is developed to calculate the vessel width. This paper evaluates the accuracy of the proposed RETC algorithm, and experimental results show that the mean absolute error between the vessel width obtained by our algorithm and the reference vessel width is as low as 0.36, with a variance of only 0.10, which can be significantly reduced compared to traditional calculation measurements.
Original languageEnglish
Article number801
Number of pages27
JournalBioengineering
Volume11
Issue number8
Early online date7 Aug 2024
DOIs
Publication statusPublished - 7 Aug 2024

Data Availability Statement

The data presented in this study are available on request from the corresponding author, Haoting Liu.

Keywords

  • near-infrared image
  • vascular width
  • image enhancement
  • skeleton extraction
  • edge detection
  • geometric characteristics
  • APSLSE image segmentation
  • radius estimation of tangent circle (RETC)

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