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Inference of Tissue Haemoglobin Concentration from Stereo RGB

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Medical Imaging and Augmented Reality (MIAR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9805))

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Abstract

Multispectral imaging (MSI) can provide information about tissue oxygenation, perfusion and potentially function during surgery. In this paper we present a novel, near real-time technique for intrinsic measurements of total haemoglobin (THb) and blood oxygenation (SO\(_2\)) in tissue using only RGB images from a stereo laparoscope. The high degree of spectral overlap between channels makes inference of haemoglobin concentration challenging, non-linear and under constrained. We decompose the problem into two constrained linear sub-problems and show that with Tikhonov regularisation the estimation significantly improves, giving robust estimation of the THb. We demonstrate by using the co-registered stereo image data from two cameras it is possible to get robust SO\(_2\) estimation as well. Our method is closed from, providing computational efficiency even with multiple cameras. The method we present requires only spectral response calibration of each camera, without modification of existing laparoscopic imaging hardware. We validate our technique on synthetic data from Monte Carlo simulation and further, in vivo, on a multispectral porcine data set.

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References

  1. EMVA standard 1288: Standard for Characterization of Image Sensors andCameras. European Machine Vision Association (3.0) (2010). www.emva.org/wp-content/uploads/EMVA1288-3.0.pdf

  2. Bashkatov, A.N., Genina, E.A., Kochubey, V.I., Rubtsov, V.S., Kolesnikova, E.A., Tuchin, V.V.: Optical properties of human colon tissues in the 350–2500 nm spectral range. Quant. Electron. 44(8), 779–784 (2014)

    Article  Google Scholar 

  3. Bosschaart, N., Edelman, G.J., Aalders, M.C.G., van Leeuwen, T.G., Faber, D.J.: A literature review and novel theoretical approach on the optical propertiesof whole blood. Lasers Med. Sci. 29(2), 453–479 (2013). http://dx.doi.org/10.1007/s10103-013-1446-7

    Article  Google Scholar 

  4. Bro, R., Jong, S.D.: A fast non-negativity-constrained least squares algorithm. J. Chemometr. 11(5), 393–401 (1997)

    Article  Google Scholar 

  5. Clancy, N.T., Arya, S., Stoyanov, D., Singh, M., Hanna, G.B., Elson, D.S.: Intraoperative measurement of bowel oxygen saturation using a multispectral imaging laparoscope. Biomed. Opt. Express 6(10), 4179 (2015)

    Article  Google Scholar 

  6. Clancy, N.T., Saso, S., Stoyanov, D., Sauvage, V., Corless, D.J., Boyd, M., Noakes, D.E., Thum, M.Y., Ghaem-Maghami, S., Smith, J.R., Elson, D.S.: Multispectral imaging of organ viability during uterine transplantation surgery. In: Advanced Biomedical and Clinical Diagnostic Systems XII. SPIE-The International Society for Optical Engineering, February 2014. http://dx.doi.org/10.1117/12.2040518

  7. Clancy, N.T., Stoyanov, D., James, D.R.C., Marco, A.D., Sauvage, V., Clark, J., Yang, G.Z., Elson, D.S.: Multispectral image alignment using a three channel endoscope in vivo during minimally invasive surgery. Biomed. Opt. Express 3(10), 2567–2578 (2012). http://www.opticsinfobase.org/boe/abstract.cfm?URI=boe-3-10-2567

    Article  Google Scholar 

  8. Claridge, E., Hidović-Rowe, D., Taniere, P., Ismail, T.: Quantifying mucosal blood volume fraction from multispectral images of the colon. In: Medical Imaging, p. 65110C. International Society for Optics and Photonics (2007)

    Google Scholar 

  9. Darzi, A., Mackay, S.: Recent advances in minimal access surgery. Br. Med. J. 324(7328), 31 (2002)

    Article  Google Scholar 

  10. Du, X., Allan, M., Dore, A., Ourselin, S., Hawkes, D.J., Kelly, D.S.: Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery. Int. J. Comput. Assist. Radiol. Surg. 11(6), 1109–1119 (2015)

    Article  Google Scholar 

  11. Dunn, A.K., Devor, A., Dale, A.M., Boas, D.A.: Spatial extent of oxygen metabolism and hemodynamic changes during functional activation of the rat somatosensory cortex. NeuroImage 27(2), 279–290 (2005). http://dx.doi.org/10.1016/j.neuroimage.2005.04.024

    Article  Google Scholar 

  12. Fang, Q.: Mesh-based Monte Carlo method using fast ray-tracing in plücker coordinates. Biomed. Opt. Express 1(1), 165 (2010)

    Article  MathSciNet  Google Scholar 

  13. Fawzy, Y., Lam, S., Zeng, H.: Rapid multispectral endoscopic imaging system for near real-time mapping of the mucosa blood supply in the lung. Biomed. Opt. Express 6(8), 2980 (2015)

    Article  Google Scholar 

  14. Guazzi, A.R., Villarroel, M., Jorge, J., Daly, J., Frise, M.C., Robbins, P.A., Tarassenko, L.: Non-contact measurement of oxygen saturation with an RGB camera. Biomed. Opt. Express 6(9), 3320 (2015)

    Article  Google Scholar 

  15. Hardeberg, J.Y., Brettel, H., Schmitt, F.J.M.: Spectral characterization of electronic cameras. In: Bares, J. (ed.) Electronic Imaging: Processing, Printing, and Publishing in Color. SPIE-The International Society for Optical Engineering, September 1998. http://dx.doi.org/10.1117/12.324101

  16. Nighswander-Rempel, S.P., Shaw, R.A., Mansfield, J.R., Hewko, M., Kupriyanov, V.V., Mantsch, H.H.: Regional variations in myocardial tissue oxygenation mapped by near-infrared spectroscopic imaging. J. Mol. Cell. Cardiol. 34(9), 1195–1203 (2002)

    Article  Google Scholar 

  17. Nishidate, I., Maeda, T., Niizeki, K., Aizu, Y.: Estimation of melanin and hemoglobin using spectral reflectance images reconstructed from a digital RGB image by the Wiener estimation method. Sensors 13(6), 7902–7915 (2013)

    Article  Google Scholar 

  18. Sorg, B.S., Moeller, B.J., Donovan, O., Cao, Y., Dewhirst, M.W.: Hyperspectral imaging of hemoglobin saturation in tumor microvasculature and tumor hypoxia development. J. Biomed. Opt. 10(4), 044004 (2005)

    Article  Google Scholar 

  19. Wirkert, S.J., Clancy, N.T., Stoyanov, D., Arya, S., Hanna, G.B., Schlemmer, H.-P., Sauer, P., Elson, D.S., Maier-Hein, L.: Endoscopic sheffield index for unsupervised in vivo spectral band selection. In: Luo, X., Reich, T., Mirota, D., Soper, T. (eds.) CARE 2014. LNCS, vol. 8899, pp. 110–120. Springer, Heidelberg (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Centre for Medical Image Computing, University College London, London, UK

    Geoffrey Jones, Simon Arridge & Danail Stoyanov

  2. The Hamlyn Centre, Institute of Global Health Innovation, Imperial College London, London, UK

    Neil T. Clancy & Daniel S. Elson

  3. Department of Surgery and Cancer, Imperial College London, London, UK

    Neil T. Clancy & Daniel S. Elson

Authors
  1. Geoffrey Jones
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  2. Neil T. Clancy
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  3. Simon Arridge
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  4. Daniel S. Elson
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  5. Danail Stoyanov
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Corresponding author

Correspondence to Geoffrey Jones .

Editor information

Editors and Affiliations

  1. Institute for Surgical Technology, University of Bern, Bern, Switzerland

    Guoyan Zheng

  2. Tsinghua University, Tokyo, Japan

    Hongen Liao

  3. Faculte de Medicine, Universite de Rennes 1, Rennes Cedex, France

    Pierre Jannin

  4. University of Basel, Allschwil, Switzerland

    Philippe Cattin

  5. Hamlyn Centre, Imperial College London, London, United Kingdom

    Su-Lin Lee

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© 2016 Springer International Publishing Switzerland

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Jones, G., Clancy, N.T., Arridge, S., Elson, D.S., Stoyanov, D. (2016). Inference of Tissue Haemoglobin Concentration from Stereo RGB. In: Zheng, G., Liao, H., Jannin, P., Cattin, P., Lee, SL. (eds) Medical Imaging and Augmented Reality. MIAR 2016. Lecture Notes in Computer Science(), vol 9805. Springer, Cham. https://doi.org/10.1007/978-3-319-43775-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-43775-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-43774-3

  • Online ISBN: 978-3-319-43775-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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