Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/52000

TitleBrain tumour segmentation based on extremely randomized forest with high-level features
Author(s)Pinto, Adriano
Pereira, Sergio
Correia, J. H.
Oliveira, Jorge
Rasteiro, Deolinda M. L. D.
Silva, Carlos A.
Issue date2015
PublisherIEEE
JournalIEEE Engineering in Medicine and Biology Society Conference Proceedings
Abstract(s)Gliomas are among the most common and aggressive brain tumours. Segmentation of these tumours is important for surgery and treatment planning, but also for follow-up evaluations. However, it is a difficult task, given that its size and locations are variable, and the delineation of all tumour tissue is not trivial, even with all the different modalities of the Magnetic Resonance Imaging (MRI). We propose a discriminative and fully automatic method for the segmentation of gliomas, using appearance-and context-based features to feed an Extremely Randomized Forest (Extra-Trees). Some of these features are computed over a non-linear transformation of the image. The proposed method was evaluated using the publicly available Challenge database from BraTS 2013, having obtained a Dice score of 0.83, 0.78 and 0.73 for the complete tumour, and the core and the enhanced regions, respectively. Our results are competitive, when compared against other results reported using the same database.
TypeConference paper
URIhttp://hdl.handle.net/1822/52000
ISBN9781424492718
DOI10.1109/EMBC.2015.7319032
ISSN1557-170X
Peer-Reviewedyes
AccessRestricted access (Author)
Appears in Collections:DEI - Artigos em atas de congressos internacionais

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