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@inproceedings{1352750,
author = {Janoušová, Eva and Schwarz, Daniel and Montana, Giovanni and Kašpárek, Tomáš},
address = {Warsaw, Los Alamitos},
booktitle = {Proceedings of the 2015 Federated Conference on Computer Science and Information Systems},
doi = {http://dx.doi.org/10.15439/2015F147},
editor = {Maria Ganzha, Leszek Maciaszek, Marcin Paprzycki},
keywords = {pattern recognition; computational neuroanatomy; classification; penalized linear discriminant analysis with resampling; deformation-based morphometry; magnetic resonance imaging; schizophrenia},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Warsaw, Los Alamitos},
isbn = {978-83-60810-66-8},
pages = {263-268},
publisher = {Polskie Towarzystwo Informatyczne, IEEE},
title = {Brain Image Classification Based on Automated Morphometry and Penalised Linear Discriminant Analysis with Resampling},
url = {https://fedcsis.org/proceedings/2015/pliks/147.pdf},
year = {2015}
}
TY - JOUR
ID - 1352750
AU - Janoušová, Eva - Schwarz, Daniel - Montana, Giovanni - Kašpárek, Tomáš
PY - 2015
TI - Brain Image Classification Based on Automated Morphometry and Penalised Linear Discriminant Analysis with Resampling
PB - Polskie Towarzystwo Informatyczne, IEEE
CY - Warsaw, Los Alamitos
SN - 9788360810668
KW - pattern recognition
KW - computational neuroanatomy
KW - classification
KW - penalized linear discriminant analysis with resampling
KW - deformation-based morphometry
KW - magnetic resonance imaging
KW - schizophrenia
UR - https://fedcsis.org/proceedings/2015/pliks/147.pdf
N2 - This paper presents a new data-driven classification pipeline for discriminating two groups of individuals based on the medical images of their brain. The algorithm combines deformation-based morphometry and penalised linear discriminant analysis with resampling. The method is based on sparse representation of the original brain images using deformation logarithms reflecting the differences in the brain in comparison to the normal template anatomy. The sparse data enables efficient data reduction and classification via the penalised linear discriminant analysis with resampling. The classification accuracy obtained in an experiment with magnetic resonance brain images of first episode schizophrenia patients and healthy controls is comparable to the related state-of-the-art studies.
ER -
JANOUŠOVÁ, Eva, Daniel SCHWARZ, Giovanni MONTANA and Tomáš KAŠPÁREK. Brain Image Classification Based on Automated Morphometry and Penalised Linear Discriminant Analysis with Resampling. Online. In Maria Ganzha, Leszek Maciaszek, Marcin Paprzycki. \textit{Proceedings of the 2015 Federated Conference on Computer Science and Information Systems}. Warsaw, Los Alamitos: Polskie Towarzystwo Informatyczne, IEEE, 2015, p.~263-268. ISBN~978-83-60810-66-8. Available from: https://dx.doi.org/10.15439/2015F147.
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