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Inference of tissue haemoglobin concentration from Stereo RGB

Jones, G; Clancy, NT; Arridge, S; Elson, DS; Stoyanov, D; (2016) Inference of tissue haemoglobin concentration from Stereo RGB. In: Zheng, G and Liao, H and Jannin, P and Cattin, P and Lee, SL, (eds.) Medical Imaging and Augmented Reality. MIAR 2016. (pp. pp. 50-58). Springer: Cham.

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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 22 ) 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 22 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.

Type: Proceedings paper
Title: Inference of tissue haemoglobin concentration from Stereo RGB
Event: Medical Imaging and Augmented Reality 2016 (MIAR 2016)
ISBN-13: 9783319437743
DOI: 10.1007/978-3-319-43775-0_5
Publisher version: https://doi.org/10.1007/978-3-319-43775-0_5
Additional information: Copyright © Springer International Publishing Switzerland 2016. The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-43775-0_5
UCL classification: UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Engineering Science
URI: http://discovery.ucl.ac.uk/id/eprint/1503723
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