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Real-time dual-modal vein imaging system

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

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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References

  1. Zeman H, Lovhoiden G, Vrancken C, Danish R (2005) Prototype vein contrast enhancer. Opt Eng 44(8):086401. https://doi.org/10.1117/1.2009763

    Article  Google Scholar 

  2. Miyake RK, Zeman HD, Duarte FH, Kikuchi R, Ramacciotti E, Lovhoiden G, Vrancken C (2006) Vein imaging: a new method of near infrared imaging, where a processed image is projected onto the skin for the enhancement of vein treatment. Dermatol Surg 32(8):1031–1038. https://doi.org/10.1111/j.1524-4725.2006.32226.x

    Article  CAS  PubMed  Google Scholar 

  3. Zharov VP, Ferguson S, Eidt JF, Howard PC, Fink LM, Waner M (2004) Infrared imaging of subcutaneous veins. Lasers Surg Med 34:56–61. https://doi.org/10.1002/lsm.10248

    Article  PubMed  Google Scholar 

  4. Fuksis R, Greitans M, Nikisins O, Pudzs M (2010) Infrared imaging system for analysis of blood vessel structure. Electron Electr Eng Kaunas Technol 97(1):45–48

    Google Scholar 

  5. Crisan S, Tarnovan JG, Crisan TE (2007) A low cost vein detection system using near infrared radiation. In: IEEE sensors applications symposium, San Diego, CA, USA. IEEE. https://doi.org/10.1109/SAS.2007.374359

  6. Mansoor M, Sravani SN, Naqvi SZ, Badshah I, Saleem M (2013) Real-time low cast infrared vein imaging system. In: International conference on signal processing, image processing and pattern recognition, Coimbatore, India, 2013. IEEE. https://doi.org/10.1109/ICSIPR.2013.6497970

  7. Paquita V, Pricea JR, Meriaudeaub F, Tobina KW, Ferrellc TL (2006) Combining near-infrared illuminants to optimize venous imaging. In: Medical imaging 2007: visualization and image-guided procedures, San Diego, CA, USA. SPIE, p 65090H. https://doi.org/10.1117/12.712576

  8. Wang L, Leedham G (2006) Near- and far-infrared imaging for vein pattern biometrics. In: IEEE international conference on video and signal based surveillance, Sydney, NSW, Australia. IEEE. https://doi.org/10.1109/AVSS.2006.80

  9. Lee EC, Jung H, Kim D (2011) New finger biometric method using near infrared imaging. Sensors 11(3):2319–2333. https://doi.org/10.3390/s110302319

    Article  CAS  PubMed  Google Scholar 

  10. Michael GKO, Connie T, Teoh ABJ (2011) A contactless biometric system using palm print and palm vein features. In: Chetty G (ed) Advanced biometric technologies. InTech, pp 155–178. https://doi.org/10.1109/icarcv.2010.5707951

  11. Cai EZ, Sankaran K, Tan M, Chan YH, Lim TC (2017) Pen torch transillumination: difficult venepuncture made easy. World J Surg 41:2401–2408. https://doi.org/10.1007/s00268-017-4050-3

    Article  PubMed  Google Scholar 

  12. Cuper NJ, Klaessens JH, Jaspers JE, de Roodea R, Noordmans HJ, de Graaff JC, Verdaasdonk RM (2013) The use of near-infrared light for safe and effective visualization of subsurface blood vessels to facilitate blood withdrawal in children. Med Eng Phys 35:433–440. https://doi.org/10.1016/j.medengphy.2012.06.007

    Article  PubMed  Google Scholar 

  13. Ai D, Yang J, Fan J, Zhao Y, Song X, Shen J, Shao L, Wang Y (2016) Augmented reality based real-time subcutaneous vein imaging system. Biomed Opt 7(7):2565–2585. https://doi.org/10.1364/BOE.7.002565

    Article  Google Scholar 

  14. Francis M, Jose A, Devadhas G, Avinashe K (2017) A novel technique for forearm blood vein detection and enhancement. Biomed Res 28(7):2913–2919

    Google Scholar 

  15. Seker K, Engin M (2016) Deep tissue near-infrared imaging for vascular network analysis. J Innov Opt Health Sci. https://doi.org/10.1142/s1793545816500516

    Article  Google Scholar 

  16. Kim D, Kim Y, Yoon S, Lee D (2017) Preliminary study for designing a novel vein-visualizing device. Sensors. https://doi.org/10.3390/s17020304

    Article  PubMed  Google Scholar 

  17. Lee S, Park S, Lee D (2013) A phantom study on the propagation of NIR rays under the skin for designing a novel vein-visualizing device. In: 13th international conference on control, automation and systems, Gwangui, Korea. IEEE. https://doi.org/10.1109/ICCAS.2013.6704026

  18. Prasad PN (2003) Introduction to biophotonics. Wiley, Hoboken

    Book  Google Scholar 

  19. Newman A (1976) Photographic techniques in scientific research, vol 2. Academic Press, Cambridge

    Google Scholar 

  20. Wang L, Leedham G, Choa DS-Y (2008) Minutiae feature analysis for infrared hand vein pattern biometrics. Pattern Recogn 41:920–929. https://doi.org/10.1016/j.patcog.2007.07.012

    Article  Google Scholar 

  21. Chen L, Wang J, Yang S, He H (2017) A finger vein image-based personal identification system with self-adaptive illuminance control. IEEE Trans Instrum Meas 66(2):294–304. https://doi.org/10.1109/tim.2016.2622860

    Article  Google Scholar 

  22. Kaddoum R, Anghelescu D, Parish M, Wright B, Trujillo L, Wu J, Wu Y, Burgoyne L (2012) A randomized controlled trial comparing the AccuVein AV300 device to standard insertion technique for intravenous cannulation of anesthetized children. Paediatr Anaesth 22(9):884–889. https://doi.org/10.1111/j.1460-9592.2012.03896.x

    Article  PubMed  Google Scholar 

  23. Chu MW, Sarik JR, Wu LC, Serletti JM, Bank J (2016) Non-invasive imaging of preoperative mapping of superficial veins in free flap breast reconstruction. Arch Plast Surg 43:119–121. https://doi.org/10.5999/aps.2016.43.1.119

    Article  PubMed  PubMed Central  Google Scholar 

  24. Hebden JC, Alkhaja A, Mahe L, Powell S, Everdell N (2015) Measurement of contrast of phantom and in vivo subsurface blood vessels using two near-infrared imaging systems. In: Optical diagnostics and sensing XV: toward point-of-care diagnostics, San Francisco, CA, USA. SPIE, p 933213. https://doi.org/10.1117/12.2084673

  25. Wang F, Behrooz A, Morris M, Adibi A (2013) High-contrast subcutaneous vein detection and localization using multispectral imaging. J Biomed Opt. https://doi.org/10.1117/1.JBO.18.5.050504

    Article  PubMed  PubMed Central  Google Scholar 

  26. Paquit V, Tobin K, Price J, Mèriaudeau F (2009) 3D and multispectral imaging for subcutaneous veins detection. Opt Express 16(14):11360–11365. https://doi.org/10.1109/ICIP.2009.5414511

    Article  Google Scholar 

  27. Chen AI, Balter ML, Maguire TJ, Yarmush ML (2016) 3D near infrared and ultrasound imaging of peripheral blood vessels for real-time localization and needle guidance. In: Ourselin S, Joskowicz L, Sabuncu M, Unal G, Wells W (eds) Medical image computing and computer-assisted intervention, Athens, Greece. Lecture notes in computer science. Springer, pp 388–396. https://doi.org/10.1007/978-3-319-46726-9_45

    Google Scholar 

  28. Ahmed T, Rahman KS, Shawlin SS, Hasan M, Bhattacharjee A, Fattah SA, Shahnaz C (2017) Real time injecting device with automated robust vein detection using near infrared camera and live video. In: Global humanitarian technology conference (GHTC), San Jose, CA, USA. IEEE. https://doi.org/10.1109/GHTC.2017.8239298

  29. Katsogridakis Y, Seshadri R, Sullivan C, Waltzman M (2008) Veinlite transillumination in the pediatric emergency department: a therapeutic interventional trial. Pediatr Emerg Care 24:83–88. https://doi.org/10.1097/PEC.0b013e318163db5f

    Article  PubMed  Google Scholar 

  30. Nizamoglu M, Tan A, Gerrish H, Barnes D, Dziewulski P (2016) Infrared technology to improve efficacy of venous access in burns population. Eur J Plast Surg 39:37–40. https://doi.org/10.1007/s00238-015-1165-3

    Article  Google Scholar 

  31. Nakasa T, Ishikawa M, Ikuta Y, Yoshikawa M, Sawa M, Tsuyuguchi Y, Adachi N (2017) In-vivo imaging of the sentinel vein using the near-infrared vascular imaging system in hallux valgus patients. J Orthop Sci 22(6):1066–1070. https://doi.org/10.1016/j.jos.2017.07.004

    Article  PubMed  Google Scholar 

  32. Ramer L, Hunt P, Ortega E, Knowlton J, Briggs R, Hirokawa S (2016) Effect of intravenous (IV) assistive device (VeinViewer) on IV access attempts, procedural time, and patient and nurse satisfaction. J Pediatr Oncol Nurs 33(4):273–281. https://doi.org/10.1177/1043454215600425

    Article  PubMed  Google Scholar 

  33. Bandara A, Rajarata K, Giragama P (2017) Super-efficient spatially adaptive contrast enhancement algorithm for superficial vein imaging. In: IEEE international conference on industrial and information systems, Peradeniya, Sri Lanka. IEEE. https://doi.org/10.1109/iciinfs.2017.8300427

  34. Yakno M, Saleh JM, Rosdi BA (2011) Low contrast hand vein image enhancement. In: IEEE international conference on signal and image processing applications, Kuala Lumpur, Malaysia. IEEE. https://doi.org/10.1109/ICSIPA.2011.6144135

  35. Asrar M, Al-Habaibeh A, Houda M (2016) Innovative algorithm to evaluate the capabilities of visual, near infrared, and infrared technologies for the detection of veins for intravenous cannulation. Appl Opt 55(34):D67–D75. https://doi.org/10.1364/AO.55.000D67

    Article  PubMed  Google Scholar 

  36. Pizer S, Amburn E, Austin J, Cromartie R, Geselowitz A, Greer T, ter Haar Romeny B, Zimmerman J, Zuiderveld K (1987) Adaptive histogram equalization and its variations. Comput Vis Graph Image Proc 39:355–368. https://doi.org/10.1016/S0734-189X(87)80186-X

    Article  Google Scholar 

  37. Reza A (2004) Realization of the contrast limited adaptive histogram equalization (CLAHE) for real-time image enhancement. J VLSI Signal Process Syst Signal Image Video Technol 38(1):35–44. https://doi.org/10.1023/B:VLSI.0000028532.53893.82

    Article  Google Scholar 

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Acknowledgements

This study was supported in part by grants from the National Aeronautics and Space Administration (NASA Space Technology Research Fellowship NNX14AL37H), NSF Grant MCB-1616216, and the University of Akron Startup Funds.

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Correspondence to Yang Liu.

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Ethical statement

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study. Additional informed consent was obtained from all individual participants for whom identifying information is included in this article.

Electronic supplementary material

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Demonstration video of how the system works in real time. It is intuitive and user-friendly (MP4 13971 kb)

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Mela, C.A., Lemmer, D.P., Bao, F.S. et al. Real-time dual-modal vein imaging system. Int J CARS 14, 203–213 (2019). https://doi.org/10.1007/s11548-018-1865-9

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  • DOI: https://doi.org/10.1007/s11548-018-1865-9

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