Proceedings of Medical Image Understanding and Analysis 2010
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F65269705%3A_____%2F10%3A%230001216" target="_blank" >RIV/65269705:_____/10:#0001216 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Proceedings of Medical Image Understanding and Analysis 2010
Original language description
Recent studies have demonstrated that diagnostics of schizophrenia based on image data is a difficult task because of extensive overlaps of brain regions distinguishing patients with schizophrenia from healthy controls and also because of the small sample size problem. An algorithm for the automatic classification of first-episode schizophrenia patients and healthy controls based on deformations and gray matter (GM) density images extracted from their MRI intensity data is introduced here. The deformations and GM density images are reduced by principal component analysis, which is here based on the covariance matrix of persons (pPCA). The reduced image data is then classified with the use of modified maximum uncertainty linear discriminant analysis (MLDA), which gives better sensitivity than original MLDA. The classification efficiency of the proposed algorithm is comparable with other state-of-art studies in the schizophrenia research.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
FL - Psychiatry, sexology
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of Medical Image Understanding and Analysis 2010
ISBN
978-0-9566150-0-8
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
83-87
Publisher name
University of Warwick
Place of publication
Coventry (UK)
Event location
University of Warwick
Event date
Jan 1, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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