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Authors: Elisabetta Binaghi ; Massimo Omodei ; Valentina Pedoia ; Sergio Balbi ; Desiree Lattanzi and Emanuele Monti

Affiliation: Insubria University, Italy

ISBN: 978-989-758-054-3

Keyword(s): MRI Segmentation, Brain Tumor Segmentation, Meningioma, Graph Cut, Support Vector Machine.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Data Manipulation ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image Processing and Artificial Vision Applications ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Support Vector Machines and Applications ; Theory and Methods

Abstract: This work focuses the attention on the automatic segmentation of meningioma from multispectral brain Magnetic Resonance imagery. The Authors address the segmentation task by proposing a fully automatic method hierarchically structured in two phases. The preliminary unsupervised phase is based on Graph Cut framework. In the second phase, preliminary segmentation results are refined using a supervised classification based on Support Vector Machine. The overall segmentation procedure is conceived fully automatic and tailored to non-volumetric data characterized by poor inter-slice spacing, in an attempt to facilitate the insertion in clinical practice. The results obtained in this preliminary study are encouraging and prove that the segmentation benefits from the allied use of Graph Cut and Support Vector Machine frameworks.

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Paper citation in several formats:
Binaghi, E.; Omodei, M.; Pedoia, V.; Balbi, S.; Lattanzi, D. and Monti, E. (2014). Automatic Segmentation of MR Brain Tumor Images using Support Vector Machine in Combination with Graph Cut.In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014) ISBN 978-989-758-054-3, pages 152-157. DOI: 10.5220/0005068501520157

@conference{ncta14,
author={Elisabetta Binaghi. and Massimo Omodei. and Valentina Pedoia. and Sergio Balbi. and Desiree Lattanzi. and Emanuele Monti.},
title={Automatic Segmentation of MR Brain Tumor Images using Support Vector Machine in Combination with Graph Cut},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)},
year={2014},
pages={152-157},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005068501520157},
isbn={978-989-758-054-3},
}

TY - CONF

JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2014)
TI - Automatic Segmentation of MR Brain Tumor Images using Support Vector Machine in Combination with Graph Cut
SN - 978-989-758-054-3
AU - Binaghi, E.
AU - Omodei, M.
AU - Pedoia, V.
AU - Balbi, S.
AU - Lattanzi, D.
AU - Monti, E.
PY - 2014
SP - 152
EP - 157
DO - 10.5220/0005068501520157

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