Literature DB >> 30291592

Real-time dual-modal vein imaging system.

Christopher A Mela1, David P Lemmer1, Forrest Sheng Bao2, Francis Papay3, Tyler Hicks1, Yang Liu4.   

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.

Entities:  

Keywords:  Computer vision; Near-infrared; Optical imaging; Vein detection

Mesh:

Year:  2018        PMID: 30291592     DOI: 10.1007/s11548-018-1865-9

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  4 in total

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

Authors:  Wenxin Xiang; Deliang Li; Jiabing Sun; Jiawei Liu; Guowei Zhou; Yuan Gao; Xiaoyu Cui
Journal:  IEEE J Transl Eng Health Med       Date:  2021-10-14       Impact factor: 3.316

2.  U-DAVIS-Deep Learning Based Arm Venous Image Segmentation Technique for Venipuncture.

Authors:  Avik Kuthiala; Naman Tuli; Harpreet Singh; Omer F Boyraz; Neeru Jindal; Ravimohan Mavuduru; Smita Pattanaik; Prashant Singh Rana
Journal:  Comput Intell Neurosci       Date:  2022-10-04

3.  Competitive Real-Time Near Infrared (NIR) Vein Finder Imaging Device to Improve Peripheral Subcutaneous Vein Selection in Venipuncture for Clinical Laboratory Testing.

Authors:  Mark D Francisco; Wen-Fan Chen; Cheng-Tang Pan; Ming-Cheng Lin; Zhi-Hong Wen; Chien-Feng Liao; Yow-Ling Shiue
Journal:  Micromachines (Basel)       Date:  2021-03-30       Impact factor: 2.891

4.  Novel Multimodal, Multiscale Imaging System with Augmented Reality.

Authors:  Christopher Mela; Francis Papay; Yang Liu
Journal:  Diagnostics (Basel)       Date:  2021-03-04
  4 in total

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