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The HELICoiD Project: Parallel SVM for Brain Cancer Classification

Authors :
Himar Fabelo
Francesco Leporati
Giovanni Danese
Camilla Cividini
Alessandro Gatti
Samuel Ortega
Gustavo M. Callico
Emanuele Torti
Source :
DSD
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

This paper describes the challenge of real-time tumor tissue identification dealt with by the HypErspectraL Imaging Cancer Detection (HELICoiD) European project. This project was funded by the Research Executive Agency, through the Future and Emerging Technologies (FET-Open) programme, under the 7th Framework Programme of the European Union. It involved four universities, three industrial partners and two hospitals. In this paper, we focused on the activity performed by the University of Las Palmas de Gran Canaria, in collaboration with the University of Pavia, concerning the parallel implementation of Support Vector Machine (SVM) classification for tumor tissue identification during surgery. Obtained results show that this classification is real-time compliant when performed using Graphic Processing Units (GPUs).

Details

Database :
OpenAIRE
Journal :
2017 Euromicro Conference on Digital System Design (DSD)
Accession number :
edsair.doi...........1ae05046adf160bd82b872e534361bfe