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An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation

Institute for Applied Microelectronics (IUMA), University of Las Palmas de Gran Canaria (ULPGC), Las Palmas de Gran Canaria 35017, Spain
Centre of Software Technologies and Multimedia Systems (CITSEM), Technical University of Madrid (UPM), Madrid 28031, Spain
Wessex Neurological Centre, University Hospital Southampton, Tremona Road, Southampton SO16 6YD, UK
Department of Neurosurgery, Addenbrookes Hospital and University of Cambridge, Cambridge CB2 0QQ, UK
Department of Neurosurgery, University Hospital Doctor Negrin, Las Palmas de Gran Canaria 35010, Spain
The Hamlyn Centre, Imperial College London (ICL), London SW7 2AZ, UK
Laboratoire CRISTAL, Université Lille 3, Villeneuve-d’Ascq 59653, France
Ecole Nationale Supérieure des Mines de Paris (ENSMP), MINES ParisTech, Paris 75006, France
Author to whom correspondence should be addressed.
Sensors 2018, 18(2), 430;
Received: 15 December 2017 / Revised: 29 January 2018 / Accepted: 30 January 2018 / Published: 1 February 2018
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
Hyperspectral imaging (HSI) allows for the acquisition of large numbers of spectral bands throughout the electromagnetic spectrum (within and beyond the visual range) with respect to the surface of scenes captured by sensors. Using this information and a set of complex classification algorithms, it is possible to determine which material or substance is located in each pixel. The work presented in this paper aims to exploit the characteristics of HSI to develop a demonstrator capable of delineating tumor tissue from brain tissue during neurosurgical operations. Improved delineation of tumor boundaries is expected to improve the results of surgery. The developed demonstrator is composed of two hyperspectral cameras covering a spectral range of 400–1700 nm. Furthermore, a hardware accelerator connected to a control unit is used to speed up the hyperspectral brain cancer detection algorithm to achieve processing during the time of surgery. A labeled dataset comprised of more than 300,000 spectral signatures is used as the training dataset for the supervised stage of the classification algorithm. In this preliminary study, thematic maps obtained from a validation database of seven hyperspectral images of in vivo brain tissue captured and processed during neurosurgical operations demonstrate that the system is able to discriminate between normal and tumor tissue in the brain. The results can be provided during the surgical procedure (~1 min), making it a practical system for neurosurgeons to use in the near future to improve excision and potentially improve patient outcomes. View Full-Text
Keywords: hyperspectral imaging instrumentation; brain cancer detection; image processing hyperspectral imaging instrumentation; brain cancer detection; image processing
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Fabelo, H.; Ortega, S.; Lazcano, R.; Madroñal, D.; M. Callicó, G.; Juárez, E.; Salvador, R.; Bulters, D.; Bulstrode, H.; Szolna, A.; Piñeiro, J.F.; Sosa, C.; J. O’Shanahan, A.; Bisshopp, S.; Hernández, M.; Morera, J.; Ravi, D.; Kiran, B.R.; Vega, A.; Báez-Quevedo, A.; Yang, G.-Z.; Stanciulescu, B.; Sarmiento, R. An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation. Sensors 2018, 18, 430.

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