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Authors: Himar Fabelo 1 ; Samuel Ortega 1 ; Raùl Guerra 1 ; Gustavo Callicó 1 ; Adam Szolna 2 ; Juan F. Piñeiro 2 ; Miguel Tejedor 1 ; Sebastián López 1 and Roberto Sarmiento 1

Affiliations: 1 Institute for Applied Microelectronics and University of Las Palmas de Gran Canaria, Spain ; 2 University Hospital Doctor Negrín, Spain

Keyword(s): Brain Cancer Detection, Hyperspectral Imaging, Random Forest, Classification Algorithms.

Abstract: Hyperspectral Imaging is an emerging technology for medical diagnosis issues due to the fact that it is a non-contact, non-ionizing and non-invasive sensing technique. The work presented in this paper tries to establish a novel way in the use of hyperspectral images to help neurosurgeons to accurately determine the tumour boundaries in the process of brain tumour resection, avoiding excessive extraction of healthy tissue and the accidental leaving of un-resected small tumour tissues. So as to do that, a hyperspectral database of in-vivo human brain samples has been created and a procedure to label the pixels diagnosed by the pathologists has been described. A total of 24646 samples from normal and tumour tissues from 13 different patients have been obtained. A pre-processing chain to homogenize the spectral signatures has been developed, obtaining 3 types of datasets (using different pre-processing chain) in order to determine which one provides the best classification results using a Random Forest classifier. The experimental results of this supervised classification algorithm to distinguish between normal and tumour tissues have achieved more than 99% of accuracy. (More)

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Paper citation in several formats:
Fabelo, H.; Ortega, S.; Guerra, R.; Callicó, G.; Szolna, A.; Piñeiro, J.; Tejedor, M.; López, S. and Sarmiento, R. (2016). A Novel Use of Hyperspectral Images for Human Brain Cancer Detection using in-Vivo Samples. In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Smart-BIODEV; ISBN 978-989-758-170-0; ISSN 2184-4305, SciTePress, pages 311-320. DOI: 10.5220/0005849803110320

@conference{smart-biodev16,
author={Himar Fabelo. and Samuel Ortega. and Raùl Guerra. and Gustavo Callicó. and Adam Szolna. and Juan F. Piñeiro. and Miguel Tejedor. and Sebastián López. and Roberto Sarmiento.},
title={A Novel Use of Hyperspectral Images for Human Brain Cancer Detection using in-Vivo Samples},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Smart-BIODEV},
year={2016},
pages={311-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005849803110320},
isbn={978-989-758-170-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - Smart-BIODEV
TI - A Novel Use of Hyperspectral Images for Human Brain Cancer Detection using in-Vivo Samples
SN - 978-989-758-170-0
IS - 2184-4305
AU - Fabelo, H.
AU - Ortega, S.
AU - Guerra, R.
AU - Callicó, G.
AU - Szolna, A.
AU - Piñeiro, J.
AU - Tejedor, M.
AU - López, S.
AU - Sarmiento, R.
PY - 2016
SP - 311
EP - 320
DO - 10.5220/0005849803110320
PB - SciTePress