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Authors: Christophe Montagne ; Andreas Kodewitz ; Vincent Vigneron ; Virgile Giraud and Sylvie Lelandais

Affiliation: University of Evry, France

ISBN: 978-989-8565-36-5

Keyword(s): Local Binary Pattern, Feature Extraction, Positron Emission Tomographic images, Alzheimer disease, Machine Learning.

Related Ontology Subjects/Areas/Topics: Applications ; Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Biometrics ; Biometrics and Pattern Recognition ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing ; Multimedia ; Multimedia Signal Processing ; Pattern Recognition ; Telecommunications

Abstract: The early diagnostic of Alzheimer disease by non-invasive technique becomes a priority to improve the life of patient and his social environment by an adapted medical follow-up. This is a necessity facing the growing number of affected persons and the cost to our society caused by dementia. Computer based analysis of Fluorodeoxyglucose PET scans might become a possibility to make early diagnosis more efficient. Temporal and parietal lobes are the main location of medical findings. We have clues that in PET images these lobes contain more information about Alzheimer’s disease. We used a texture operator, the Local Binary Pattern, to include prior information about the localization of changes in the human brain. We use a Support Vector machine (SVM) to classify Alzheimer’s disease versus normal control group and to get better classification rates focusing on parietal and temporal lobes.

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Paper citation in several formats:
Montagne, C.; Kodewitz, A.; Vigneron, V.; Giraud, V.; Giraud, V. and Lelandais, S. (2013). 3D Local Binary Pattern for PET Image Classification by SVM - Application to Early Alzheimer Disease Diagnosis.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013) ISBN 978-989-8565-36-5, pages 145-150. DOI: 10.5220/0004226201450150

@conference{biosignals13,
author={Christophe Montagne. and Andreas Kodewitz. and Vincent Vigneron. and Virgile Giraud. and Virgile Giraud. and Sylvie Lelandais.},
title={3D Local Binary Pattern for PET Image Classification by SVM - Application to Early Alzheimer Disease Diagnosis},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)},
year={2013},
pages={145-150},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004226201450150},
isbn={978-989-8565-36-5},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2013)
TI - 3D Local Binary Pattern for PET Image Classification by SVM - Application to Early Alzheimer Disease Diagnosis
SN - 978-989-8565-36-5
AU - Montagne, C.
AU - Kodewitz, A.
AU - Vigneron, V.
AU - Giraud, V.
AU - Giraud, V.
AU - Lelandais, S.
PY - 2013
SP - 145
EP - 150
DO - 10.5220/0004226201450150

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