Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/110313
Título: O-ONC-03 - Hyperspectral Imaging as a novel instrument for intraoperative brain tumor detection
Autores/as: Szolna, Adam 
Mortar, Jesus
Marrero Callicó, Gustavo 
Fabelo, Himar 
Ortega, Samuel 
Clasificación UNESCO: 3314 Tecnología médica
Palabras clave: Brain tumor
Hyperspectral images
Intraoperative visualization
Fecha de publicación: 2016
Publicación seriada: Neurocirugia 
Conferencia: Congresso Internacional de Neurocirurgia-Congreso Internacional de Neurocirugía. Neuroiberia 2016 Portugal, 11-14 Mayo 2016
Resumen: Objectives: Direct visualization of brain tumors using hyperspectral cameras (HSC) as an original non-invasive intraoperative imaging method. Material and methods: A hyperspectral imaging (HSI) is a technology based on a large number of small bands of the electromagnetic spectrum. The HSI of different tissue forms usually its own, characteristic pattern at certain frequencies that provides a potential approach to distinguish these tissues in a much bigger wavelength band than that of a human eye. This project develops an experimental intraoperative setup based on HSC and set of algorithms capable of discrimination healthy and pathological tissues during human brain tumor surgery. Reflected light is sampled using the HSC, processes and eventually provides to the surgeon analisis and compare to the pathological results of the sample obtained from the same aeras of the surgical field where the HSC registration was done. Spectral classification of the captured HSI was defined by Random Forest classifier and employed by supervised learning algorithm. The labelling of samples was performed using two levels: “normal - tumor tissue” and “primary - secondary tumor”. Results: The experimental results were based on the HSI of 22 brain surgeries and about 30,000 imaging samples, using sensitivity, specificity and overall acuracy metrics. Using the whole pre-processing chain, the automatic discrimination between normal and tumor sample maintain > 99% accurate. Conclusions: The preliminary results of the application of HSI in the brain tumor detection confirm high ability in accurate and automatic discrimination between different types of tissue during the brain oncological surgery.
URI: http://hdl.handle.net/10553/110313
ISSN: 1130-1473
Fuente: Neurocirugia [ISSN 1130-1473], n. 27
Colección:Actas de congresos
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