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@article{1105537,
author = {Schwarz, Daniel and Kašpárek, Tomáš},
article_number = {1},
doi = {http://dx.doi.org/10.1016/j.inffus.2013.02.002},
keywords = {image registration; brain morphometry; pattern recognition; computational neuroanatomy; group analysis; schizophrenia},
language = {eng},
issn = {1566-2535},
journal = {Information Fusion},
title = {Brain morphometry of MR images for automated classification of first-episode schizophrenia},
volume = {19},
year = {2014}
}
TY - JOUR
ID - 1105537
AU - Schwarz, Daniel - Kašpárek, Tomáš
PY - 2014
TI - Brain morphometry of MR images for automated classification of first-episode schizophrenia
JF - Information Fusion
VL - 19
IS - 1
SP - 97-102
EP - 97-102
PB - ELSEVIER SCIENCE BV
SN - 15662535
KW - image registration
KW - brain morphometry
KW - pattern recognition
KW - computational neuroanatomy
KW - group analysis
KW - schizophrenia
N2 - Schizophrenia is a disabling psychiatric disorder that usually begins to affect individuals during their adolescence or early adulthood and most patients continue to suffer social, economic, and psychological difficulties from the very onset of the disorder. The neurobiology of the disorder comprises of changes in the brain that can be detected using MR imaging. Focus on the morphological changes in patients with first episode schizophrenia limits the confouding effect of factors such as long-term medication or progression. Therefore, the detected abnormalities are more likely to indicate the primary pathology and the existence of such changes provides the opportunity of applying them for subject recognition based on brain imaging.
ER -
SCHWARZ, Daniel a Tomáš KAŠPÁREK. Brain morphometry of MR images for automated classification of first-episode schizophrenia. \textit{Information Fusion}. ELSEVIER SCIENCE BV, 2014, roč.~19, č.~1, s.~97-102. ISSN~1566-2535. Dostupné z: https://dx.doi.org/10.1016/j.inffus.2013.02.002.
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