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Authors: Jaroslav Rokicki 1 ; Hiyoshi Kazuko 2 ; Francois-Benoit Vialatte 3 ; Andrius Ušinskas 4 and Andrzej Cichocki 5

Affiliations: 1 Vilnius Gediminas Technical University, Brain Science Institute and RIKEN, Lithuania ; 2 Vilnius Gediminas Technical University and Kyoto University Graduate School of Medicine, Lithuania ; 3 ESPCI ParisTech, France ; 4 Vilnius Gediminas Technical University, Lithuania ; 5 Brain Science Institute and RIKEN, Japan

ISBN: 978-989-8565-33-4

Keyword(s): Alzheimer’s Disease, Brain Atrophy, Segmentation of Brain Subnetworks, Hippocampus, Amygdala, Entorhinal Cortex, Multi-volume, Classification, LDA, Early Detection.

Abstract: Alzheimer’s disease is neurodegenerative disorder believed to affect 24.3 million people worldwide. Proposed MRI based disease progression markers have shown ability to perform the classification between the Alzheimer’s Disease (AD), Mild Cognitive Impariment (MCI) and Normal Cognitive (NC) subjects. We exploited two approaches, first one is to use single sub-network volume as a feature, second to use a network of most discriminative sub-networks. Multi-feature approach showed improvement by 4.5% in AD/NC classification case, and 1.5 % in MCI/NC case. Study was summarized for 48 AD, 119 MCI and 66 NC subjects.

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Paper citation in several formats:
Rokicki J., Kazuko H., Vialatte F., Ušinskas A. and Cichocki A. (2012). Early Alzheimer’s Disease Progression Detection using Multi-subnetworks of the Brain.In Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: SSCN, (IJCCI 2012) ISBN 978-989-8565-33-4, pages 684-691. DOI: 10.5220/0004182806840691

@conference{sscn12,
author={Jaroslav Rokicki and Hiyoshi Kazuko and Francois-Benoit Vialatte and Andrius Ušinskas and Andrzej Cichocki},
title={Early Alzheimer’s Disease Progression Detection using Multi-subnetworks of the Brain},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: SSCN, (IJCCI 2012)},
year={2012},
pages={684-691},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004182806840691},
isbn={978-989-8565-33-4},
}

TY - CONF

JO - Proceedings of the 4th International Joint Conference on Computational Intelligence - Volume 1: SSCN, (IJCCI 2012)
TI - Early Alzheimer’s Disease Progression Detection using Multi-subnetworks of the Brain
SN - 978-989-8565-33-4
AU - Rokicki J.
AU - Kazuko H.
AU - Vialatte F.
AU - Ušinskas A.
AU - Cichocki A.
PY - 2012
SP - 684
EP - 691
DO - 10.5220/0004182806840691

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