Automatic Generation of Suitable DWT Sub-band - An Application to Brain MRI Classification

Mohamed Mokhtar Bendib, Hayet Farida Merouani, Fatma Diaba

Abstract

This paper addresses the Brain MRI (Magnetic Resonance Imaging) classification problem from a new point of view. Indeed, most of the works reported in the literature follow the subsequent methodology: 1) Discrete Wavelet Transform (DWT) application, 2) sub-band selection, 3) feature extraction, and 4) learning. Consequently, those methods are limited by the information contained on the selected DWT outputs (sub-bands). This paper addresses the possibility of creating new suitable DWT sub-bands (by combining the classical DWT sub-bands) using Genetic Programming (GP) and a Random Forest (RF) classifier. These could be employed to efficiently address different classification scenarios (normal versus pathological, one versus all, and even multiclassification) as well as other automatic tasks.

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Paper Citation


in Harvard Style

Bendib M., Merouani H. and Diaba F. (2015). Automatic Generation of Suitable DWT Sub-band - An Application to Brain MRI Classification . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 166-170. DOI: 10.5220/0005333001660170


in Bibtex Style

@conference{visapp15,
author={Mohamed Mokhtar Bendib and Hayet Farida Merouani and Fatma Diaba},
title={Automatic Generation of Suitable DWT Sub-band - An Application to Brain MRI Classification},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={166-170},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005333001660170},
isbn={978-989-758-091-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - Automatic Generation of Suitable DWT Sub-band - An Application to Brain MRI Classification
SN - 978-989-758-091-8
AU - Bendib M.
AU - Merouani H.
AU - Diaba F.
PY - 2015
SP - 166
EP - 170
DO - 10.5220/0005333001660170