Informace o publikaci

Brain Image Classification Based on Automated Morphometry and Penalised Linear Discriminant Analysis with Resampling

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JANOUŠOVÁ Eva SCHWARZ Daniel MONTANA Giovanni KAŠPÁREK Tomáš

Rok publikování 2015
Druh Článek ve sborníku
Konference Proceedings of the 2015 Federated Conference on Computer Science and Information Systems
Fakulta / Pracoviště MU

Lékařská fakulta

Citace
www https://fedcsis.org/proceedings/2015/pliks/147.pdf
Doi http://dx.doi.org/10.15439/2015F147
Obor Informatika
Klíčová slova pattern recognition; computational neuroanatomy; classification; penalized linear discriminant analysis with resampling; deformation-based morphometry; magnetic resonance imaging; schizophrenia
Popis 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.

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