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Biomedical Engineering / Biomedizinische Technik

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering and the German Society of Biomaterials

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Habibović, Pamela / Haueisen, Jens / Jahnen-Dechent, Wilhelm / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Lenarz, Thomas / Leonhardt, Steffen / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Boenick, Ulrich / Jaramaz, Branislav / Kraft, Marc / Lenthe, Harry / Lo, Benny / Mainardi, Luca / Micera, Silvestro / Penzel, Thomas / Robitzki, Andrea A. / Schaeffter, Tobias / Snedeker, Jess G. / Sörnmo, Leif / Sugano, Nobuhiko / Werner, Jürgen /

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IMPACT FACTOR 2017: 1.096
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Online
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1862-278X
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Volume 63, Issue 5

Issues

Volume 57 (2012)

LED for hyperspectral imaging – a new selection method

Tobias Heimpold
  • Institute of Electromechanical and Electronic Design, Faculty of Electrical and Computer Engineering, Dresden University of Technology, Helmholtzstr. 10, D-01069 Dresden, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Frank Reifegerste
  • Corresponding author
  • Institute of Electromechanical and Electronic Design, Faculty of Electrical and Computer Engineering, Dresden University of Technology, Helmholtzstr. 10, D-01069 Dresden, Germany, Phone: +49 351 463 36296, Fax: +49 351 463 37183
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Stefan Drechsel
  • Institute of Electromechanical and Electronic Design, Faculty of Electrical and Computer Engineering, Dresden University of Technology, Helmholtzstr. 10, D-01069 Dresden, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jens Lienig
  • Institute of Electromechanical and Electronic Design, Faculty of Electrical and Computer Engineering, Dresden University of Technology, Helmholtzstr. 10, D-01069 Dresden, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2018-09-24 | DOI: https://doi.org/10.1515/bmt-2017-0120

Abstract

Hyperspectral imaging (HSI) has become a sophisticated technique in modern applications such as food analyses, recycling technology, medicine, pharmacy and forensic science. It allows one to analyse both spatial and spectral information from an object. But hyperspectral cameras are still expensive due to their extended wavelength range. The development of new light-emitting diodes (LED) in the recent past enables another approach to HSI using a monochrome camera in combination with a LED-based illumination. However, such a system has a lower spectral resolution. Additionally, the growing supply of LED on the market complicates the selection of LED. In this paper, we propose a new time efficient selection method for the design process of an illumination. It chooses an optimised LED combination from an existing database to match a predefined spectral power distribution. Therefore, an algorithm is used to evaluate various LED combinations. Furthermore, the method considers the spectral behaviour of each LED in dependence of forward current and temperature of the solder point. Our method has already shown promise during the selection process for even spectral distributions which is demonstrated in the study. Additionally, we will show its potential for HSI illuminations.

Keywords: design process; illumination; light-emitting diodes; multiplexed; multispectral

References

  • [1]

    Lu G, Fei B. Medical hyperspectral imaging: a review. J Biomed Opt 2014;19:010901.Google Scholar

  • [2]

    Gendrin C, Roggo Y, Collet C. Content uniformity of pharmaceutical solid dosage forms by near infrared hyperspectral imaging: a feasibility study. Talanta 2007;73:733–41.Google Scholar

  • [3]

    Gowen A, O’Donnell C, Cullen P, Downey G, Frias J. Hyperspectral imaging – an emerging process analytical tool for food quality and safety control. Trends Food Sci Technol 2007;18:590–8.Google Scholar

  • [4]

    Serranti S, Gargiulo A, Bonifazi G. Characterization of post-consumer polyolefin wastes by hyperspectral imaging for quality control in recycling processes. Waste Manage 2011;31:2217–27.Google Scholar

  • [5]

    Edelman G, Gaston E, van Leeuwen T, Cullen P, Aalders M. Hyperspectral imaging for non-contact analysis of forensic traces. Forensic Sci Int 2012;223:28–39.Google Scholar

  • [6]

    Akbari H, Halig LV, Schuster DM, Osunkoya A, Master V, Nieh PT, et al. Hyperspectral imaging and quantitative analysis for prostate cancer detection. J Biomed Opt 2012;17:076005-1-10.Google Scholar

  • [7]

    Akbari H, Uto K, Kosugi Y, Kojima K, Tanaka N. Cancer detection using infrared hyperspectral imaging. Cancer Sci 2011;102:852–7.Google Scholar

  • [8]

    Pratavieira S, Andrade C, Salvio A, Bagnato V, Kurachi C. Optical imaging as auxiliary tool in skin cancer diagnosis. In: Skin Cancers – Risk Factors, Prevention and Therapy. Rijeka, Croatia: InTech; 2011:159–72.Google Scholar

  • [9]

    Vo-Dinh T. A hyperspectral imaging system for in vivo optical diagnostics. IEEE Eng Med Biol 2004;23:40–9.Google Scholar

  • [10]

    Schweizer J, Hollmach J, Steiner G, Knels L, Funk RH, Koch E. Hyperspectral imaging – a new modality for eye diagnostics. Biomed Eng Biomed Tech 2012;57:293–6.Google Scholar

  • [11]

    Brydegaard M, Guan Z, Svanberg S. Broad-band multispectral microscope for imaging transmission spectroscopy employing an array of light-emitting diodes. Am J Phys 2009;77:104–10.Google Scholar

  • [12]

    Harvey AR, Lawlor J, McNaught AI, Williams JW, Fletcher-Holmes DW. Hyperspectral imaging for the detection of retinal disease. Proc SPIE 2002;4816:325–35.Google Scholar

  • [13]

    Everdell N, Styles I, Claridge E, Hebden J, Calcagni A. Multispectral imaging of the ocular fundus using LED illumination. Rev Sci Instrum 2010;81:093706.Google Scholar

  • [14]

    Koprowski R, Wilczyʼnski S, Wróbel Z, Kasperczyk S, Błońska-Fajfrowska B. Automatic method for the dermatological diagnosis of selected hand skin features in hyperspectral imaging. Biomed Eng Online 2014;13:47.Google Scholar

  • [15]

    Klaessens J, De Roode R, Verdaasdonk RM, Noordmans HJ. Hyperspectral imaging system for imaging O2Hb and HHb concentration changes in tissue for various clinical applications. Proc SPIE 2011;7890:78900R–10R.Google Scholar

  • [16]

    Zoueu JT, Ouattara S, Toure A, Safi S, Zan ST. Spectroscopic approach of multispectral imaging of plasmodium falciparum-infected human erythrocytes. 2009 3rd ICTON Mediterranean Winter Conference (ICTON-MW), Angers, France; 2009:1–7.Google Scholar

  • [17]

    Sobottka SB, Meyer T, Kirsch M, Koch E, Steinmeier R, Morgenstern U, et al. Intraoperative optical imaging of intrinsic signals: a reliable method for visualizing stimulated functional brain areas during surgery. J Neurosurg 2013;119:853–63.Google Scholar

  • [18]

    Panasyuk SV, Yang S, Faller DV, Ngo D, Lew RA, Freeman JE, et al. Medical hyperspectral imaging to facilitate residual tumor identification during surgery. Cancer Biol Ther 2007;6:439–46.Google Scholar

  • [19]

    Schmitt F. Multispectral color image capture using a liquid crystal tunable filter. Opt Eng 2002;41:25–32.Google Scholar

  • [20]

    Shrestha R, Hardeberg JY, Khan R. Spatial arrangement of color filter array for multispectral image acquisition. In: Widenhorn R, Nguyen V, editors. Sensors, Cameras, and Systems for Industrial, Scientific, and Consumer Applications XII. San Francisco Airport, CA, USA: SPIE; 2011.Google Scholar

  • [21]

    Park JI, Lee MH, Grossberg MD, Nayar SK. Multispectral imaging using multiplexed illumination. IEEE 11th International Conference on Computer Vision, Rio de Janeiro, Brazil; 2007:1–8.Google Scholar

  • [22]

    Reifegerste F, Lienig J. Modelling of the temperature and current dependence of LED spectra. J Light Visual Environ 2008;32:288–94.Google Scholar

  • [23]

    Barnhill R. Coons’ patches. Comput Ind 1982;3:37–43.Google Scholar

  • [24]

    Schwarz HR, Köckler N. Numerische Mathematik. 8th ed. Wiesbaden: Vieweg&Teubner; 2009.Google Scholar

  • [25]

    Weicker K. Evolutionäre Algorithmen/Lehrbuch. 3rd ed. Wiesbaden: Springer Vieweg; 2015.Google Scholar

  • [26]

    Henker S, Schlüssler J-U, Schüffny R. Concept of Color Correction on Multi-Channel CMOS Sensors. Sydney, Australia: DICTA; 2003:771–80.Google Scholar

  • [27]

    Henker S, Schlüssler J-U, Schüffny R. White Balancing with Multi-Channel CMOS Sensors. Proceedings Image and Vision Computing, New Zealand; 2005.Google Scholar

About the article

Received: 2017-07-19

Accepted: 2018-09-04

Published Online: 2018-09-24

Published in Print: 2018-10-25


Author Statement

Research funding: Authors state no funding involved.

Conflict of interest: Authors state no conflict of interest.

Informed consent: Informed consent is not applicable.

Ethical approval: The conducted research is not related to either human or animals use.


Citation Information: Biomedical Engineering / Biomedizinische Technik, Volume 63, Issue 5, Pages 529–535, ISSN (Online) 1862-278X, ISSN (Print) 0013-5585, DOI: https://doi.org/10.1515/bmt-2017-0120.

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