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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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