dc.contributor.author | Rokicki, Jaroslav | |
dc.contributor.author | Kazuko, Hiyoshi | |
dc.contributor.author | Vialatte, Francois-Benoit | |
dc.contributor.author | Ušinskas, Andrius | |
dc.contributor.author | Cichocki, Andrzej | |
dc.date.accessioned | 2023-09-18T19:19:42Z | |
dc.date.available | 2023-09-18T19:19:42Z | |
dc.date.issued | 2012 | |
dc.identifier.other | (BIS)VGT02-000025372 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/138202 | |
dc.description.abstract | Alzheimer’s disease is neurodegenerative disorder believed to affect 24.3 million people worldwide. Pro- posed 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. | eng |
dc.format.extent | p. 684-691 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | INSPEC | |
dc.title | Early Alzheimer’s disease progression detectionusing multi-subnetworks of the brain | |
dc.type | Straipsnis konferencijos darbų leidinyje kitoje DB / Paper in conference publication in other DB | |
dcterms.references | 17 | |
dc.type.pubtype | P1c - Straipsnis konferencijos darbų leidinyje kitoje DB / Article in conference proceedings in other DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas Brain Science Institute, Japan | |
dc.contributor.institution | Kyoto University Graduate School of Medicine, Japan | |
dc.contributor.institution | SIGnal Processing and MAchine Learning Laboratory, ESPCIParisTech, France | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | Brain Science Institute, Japan | |
dc.contributor.faculty | Elektronikos fakultetas / Faculty of Electronics | |
dc.subject.researchfield | T 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering | |
dc.subject.en | Alzheimer’s disease | |
dc.subject.en | Brain atrophy | |
dc.subject.en | Segmentation of brain subnetworks | |
dc.subject.en | Hippocampus | |
dc.subject.en | Amygdala | |
dc.subject.en | Entorhinal cortex | |
dc.subject.en | Multi-volume | |
dc.subject.en | Classification | |
dc.subject.en | LDA | |
dc.subject.en | Early detection | |
dcterms.sourcetitle | IJCCI 2012 : 4th International Joint Conference on Computational Intelligence, Barcelona, Spain, 5-7 October, 2012 | |
dc.publisher.name | INSTICC | |
dc.publisher.city | Setubal | |
dc.identifier.elaba | 3999078 | |