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International Journal of Computer Assisted Radiology and Surgery

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05-10-2018 | Original Article

Real-time dual-modal vein imaging system

Authors: Christopher A. Mela, David P. Lemmer, Forrest Sheng Bao, Francis Papay, Tyler Hicks, Yang Liu

Published in: International Journal of Computer Assisted Radiology and Surgery | Issue 2/2019

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Abstract

Purpose

In this paper, we present a vein imaging system to combine reflectance mode visible spectrum images (VIS) with transmission mode near-infrared (NIR) images in real time. Clear vessel localization is achieved in this manner with combined NIR–VIS dual-modal imaging.

Methods

Transmission and reflectance mode optical instrumentation is used to combine VIS and NIR images. Two methods of displaying the combined images are demonstrated here. We have conducted experiments to determine the system’s resolution, alignment accuracy, and depth penetration. Vein counts were taken from the hands of test subjects using the system and compared with vein counts taken by visual analysis.

Results

Results indicate that the system can improve vein detection in the human hand while detecting veins of a diameter < 0.5 mm at any working distance and of a 0.25 mm diameter at an optimal working distance of about 30 cm. The system has also been demonstrated to clearly detect silicone vessels with artificial blood of diameter 2, 1, and 0.5 mm diameter under a tissue depth of 3 mm. In a study involving 25 human subjects, we have demonstrated that vein visibility was significantly increased using our system.

Conclusions

The results indicate that the device is a high-resolution solution to near-surface venous imaging. This technology can be applied for IV placement, morphological analysis for disease state detection, and biometric analysis.

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Title: Real-time dual-modal vein imaging system
Authors: Christopher A. Mela
David P. Lemmer
Forrest Sheng Bao
Francis Papay
Tyler Hicks
Yang Liu
Publication date: 05-10-2018
Publisher: Springer International Publishing
Published in: International Journal of Computer Assisted Radiology and Surgery / Issue 2/2019
Print ISSN: 1861-6410
Electronic ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-018-1865-9

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Abstract

Purpose

Methods

Results

Conclusions

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