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FPGA-Based Two-Dimensional Matched Filter Design for Vein Imaging Systems.

Wenxin Xiang1, Deliang Li1, Jiabing Sun1

  • 1College of Medicine and Biological Information EngineeringNortheastern University Shenyang 110819 China.

IEEE Journal of Translational Engineering in Health and Medicine
|November 2, 2021
PubMed
Summary
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This study developed a fast, portable near-infrared vein imaging system using a Field Programmable Gate Array (FPGA). The system significantly improves vein visualization quality and speed, aiding medical procedures like venipuncture.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging Technology

Background:

  • Venipuncture is a common procedure often complicated by poor vascular filling.
  • Augmented reality (AR) devices show potential to improve first puncture success rates.
  • Existing vein imaging systems require enhancement in image rendering quality and speed.

Purpose of the Study:

  • To develop a high-quality, real-time, portable near-infrared vein imaging system.
  • To optimize image rendering using a 2D matched filtering algorithm on an FPGA.
  • To analyze and model the impact of parameters on vascular imaging depth.

Main Methods:

  • Developed a 2D matched filtering algorithm implemented on an FPGA for parallel processing.
  • Created a handheld, portable near-infrared vein imaging device.
Keywords:
Field programmable gate array (FPGA)infrared imagematched filtervein extractionvein imaging

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  • Utilized a custom dorsal hand vein image library (200 images, 120 participants).
  • Analyzed convolution kernel parameters and exposure time effects on vascular imaging.
  • Constructed a correlation model between imaging parameters and vascular depth.

    • Main Results:

    • The proposed algorithm achieved significantly higher rendering quality compared to existing methods.
    • The system demonstrated a rendering speed of 66 frames per second (fps).
    • The developed system is twice as fast as the current fastest algorithm.
    • Evaluation indicators included Tenengrad, variance, Laplace smoothness, and standard deviation.

    Conclusions:

    • The FPGA-based 2D matched filtering algorithm enhances near-infrared vein imaging quality and speed.
    • The portable device offers a promising solution for improving venipuncture success rates.
    • Optimized parameter selection is crucial for accurate vascular depth imaging.