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

## TL;DR

This paper introduces a new method for calculating forearm blood vessel width using near-infrared images and a tangent circle radius estimation algorithm.

## Contribution

The novel RETC algorithm improves accuracy in measuring vascular width compared to traditional methods.

## Key findings

- The RETC algorithm achieved a mean absolute error of 0.36 in vessel width calculation.
- The variance of the error was 0.10, significantly lower than traditional methods.

## 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.