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Title: | The HELICoiD Project: Parallel SVM for Brain Cancer Classification | Authors: | Torti, Emanuele Cividini, Camilla Gatti, Alessandro Danese, Giovanni Leporati, Francesco Fabelo, Himar Ortega, Samuel Callicò, Gustavo Marrero |
UNESCO Clasification: | 3307 Tecnología electrónica | Keywords: | Hyperspectral imaging Support vector machines Tumors Surgery Cancer |
Issue Date: | 2017 | Journal: | 2017 Euromicro Conference On Digital System Design (Dsd) | Conference: | 20th Euromicro Conference on Digital System Design, DSD 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). | URI: | http://hdl.handle.net/10553/46810 | ISBN: | 9781538621455 | DOI: | 10.1109/DSD.2017.33 | Source: | Proceedings - 20th Euromicro Conference on Digital System Design, DSD 2017 (8049823), p. 445-450 |
Appears in Collections: | Actas de congresos |
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