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Fast estimation of haemoglobin concentration in tissue via wavelet decomposition

Jones, G; Clancy, NT; Du, X; Robu, M; Arridge, S; Elson, DS; Stoyanov, D; (2017) Fast estimation of haemoglobin concentration in tissue via wavelet decomposition. In: Descoteaux, M and Maier-Hein, L and Franz, A and Jannin, P and Collins, D and Duchesne, S, (eds.) Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017. (pp. pp. 100-108). Springer: Cham, Switzerland. Green open access

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Abstract

Tissue oxygenation and perfusion can be an indicator for organ viability during minimally invasive surgery, for example allowing real-time assessment of tissue perfusion and oxygen saturation. Multispectral imaging is an optical modality that can inspect tissue perfusion in wide field images without contact. In this paper, we present a novel, fast method for using RGB images for MSI, which while limiting the spectral resolution of the modality allows normal laparoscopic systems to be used. We exploit the discrete Haar decomposition to separate individual video frames into low pass and directional coefficients and we utilise a different multispectral estimation technique on each. The increase in speed is achieved by using fast Tikhonov regularisation on the directional coefficients and more accurate Bayesian estimation on the low pass component. The pipeline is implemented using a graphics processing unit (GPU) architecture and achieves a frame rate of approximately 15 Hz. We validate the method on animal models and on human data captured using a da Vinci stereo laparoscope.

Type: Proceedings paper
Title: Fast estimation of haemoglobin concentration in tissue via wavelet decomposition
Event: Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017. MICCAI 2017
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-66185-8_12
Publisher version: http://doi.org/10.1007/978-3-319-66185-8_12
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Minimal invasive surgery, Intraoperative imaging, Multispectral imaging
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10028867
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