NIR Imaging: Development of Digital Image Processing Algorithm for Vein Contrast Enhancement

Nikita V. Remizov (Login required)
Samara National Research University, Russian Federation

Denis S. Yakimenko
Samara National Research University, Russian Federation

Dmitry N. Artemyev
Samara National Research University, Russian Federation




DOI: 10.18287/JBPE25.11.020309

Abstract

Modern medical laboratory diagnostic methods often require venipuncture, which can be challenging when blood vessels are not visible to the naked eye. This potentially leads to errors in blood sampling and misinterpretation of test results. Optical methods in medicine, specifically, vein visualization in the near-infrared (NIR) range, are actively being developed. However, current methods face several limitations, including shallow imaging depth and low contrast. Additionally, digital image processing algorithms used in these methods are imperfect. These algorithms often have low stability and performance. In this study, an efficient and robust algorithm for digital image processing has been developed to enhance vein visualization. The proposed algorithm outperforms existing methods in terms of the effectiveness of separating pixels corresponding to veins from those associated with surrounding biotissues. The algorithm is based on efficient FFT-based operations.

Keywords

vein viewer; OpenCV; convolution; fast Fourier transform; Gaussian filter; ACE; Wallis filter; contrast enhancement

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