About: Fast brain-wide search of highly discriminative regions in medical images: an application to Alzheimer's disease

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	We propose a fast algorithm for the identification of localised brain regions from medical images that discriminate between two groups of individuals. The method is based on a combination of penalised regression and a data resampling procedure. We apply this approach to both MRI and PET images for the classification of subjects with Alzheimer's disease and mild cognitive impairment. We show that the voxels selected by the algorithm form connected brain regions which are well known to be affected by Alzheimer's disease. A linear statistical classifier trained on the selected voxels achieves cross-validated classification results that are comparable to those obtained by current state-of-the-art methodologies. We propose a fast algorithm for the identification of localised brain regions from medical images that discriminate between two groups of individuals. The method is based on a combination of penalised regression and a data resampling procedure. We apply this approach to both MRI and PET images for the classification of subjects with Alzheimer's disease and mild cognitive impairment. We show that the voxels selected by the algorithm form connected brain regions which are well known to be affected by Alzheimer's disease. A linear statistical classifier trained on the selected voxels achieves cross-validated classification results that are comparable to those obtained by current state-of-the-art methodologies. (en)
Title	Fast brain-wide search of highly discriminative regions in medical images: an application to Alzheimer's disease Fast brain-wide search of highly discriminative regions in medical images: an application to Alzheimer's disease (en)
skos:prefLabel	Fast brain-wide search of highly discriminative regions in medical images: an application to Alzheimer's disease Fast brain-wide search of highly discriminative regions in medical images: an application to Alzheimer's disease (en)
skos:notation	RIV/00216224:14110/11:00056978!RIV12-MZ0-14110___
http://linked.open...avai/riv/aktivita	P
http://linked.open...avai/riv/aktivity	P(NS10347), P(NS9893)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Janoušová, Eva
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Masarykova univerzita / Lékařská fakulta
http://linked.open...dnocenehoVysledku	199351
http://linked.open...ai/riv/idVysledku	RIV/00216224:14110/11:00056978
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Feature selection; penalised regression; sparse classification; MRI; PET; Alzheimer's disease (en)
http://linked.open.../riv/klicoveSlovo	Feature selection PET penalised regression sparse classification MRI Alzheimer's disease
http://linked.open...ontrolniKodProRIV	[5E48555BB0B2]
http://linked.open...v/mistoKonaniAkce	King's College London, UK
http://linked.open...i/riv/mistoVydani	London, United Kingdom
http://linked.open...i/riv/nazevZdroje	Proceedings of Medical Image Understanding and Analysis 2011
http://linked.open...in/vavai/riv/obor	FH
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	6 (xsd:int)
http://linked.open...vavai/riv/projekt	Modern pattern recognition methods for image data analysis in neuropsychiatric research Prediction of the outcome of initial phases of schizophrenia using brain morphology
http://linked.open...UplatneniVysledku	2011
http://linked.open...iv/tvurceVysledku	Gray, Katherine Janoušová, Eva Montana, Giovanni Rueckert, Daniel Vounou, Maria Wolz, Robin
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-07-13 (xsd:date)
number of pages	5 (xsd:int)
http://purl.org/ne...btex#hasPublisher	King's College London
https://schema.org/isbn	1-901725-41-3
http://localhost/t...ganizacniJednotka	14110

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