SCHWARZ, Daniel, Tomáš KAŠPÁREK, Ivo PROVAZNÍK and Jiří JARKOVSKÝ. A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research. IEEE Transactions on Medical Imaging. New York: IEEE, 2007, vol. 26, No 4, p. 452-461. ISSN 0278-0062.
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Basic information
Original name A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research
Name in Czech Metoda pružné registrace pro automatickou morfometrii obrazů mozku z MRI v neuropsychiatrickém výzkumu
Authors SCHWARZ, Daniel (203 Czech Republic, guarantor), Tomáš KAŠPÁREK (203 Czech Republic), Ivo PROVAZNÍK (203 Czech Republic) and Jiří JARKOVSKÝ (203 Czech Republic).
Edition IEEE Transactions on Medical Imaging, New York, IEEE, 2007, 0278-0062.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30000 3. Medical and Health Sciences
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.275
RIV identification code RIV/00216224:14110/07:00022048
Organization unit Faculty of Medicine
UT WoS 000245599200003
Keywords in English MRI;image processing;schizophrenia;image registration;computational neuroanatomy
Tags computational neuroanatomy, image processing, image registration, MRI, schizophrenia
Tags International impact, Reviewed
Changed by Changed by: doc. Ing. Daniel Schwarz, Ph.D., učo 195581. Changed: 29/6/2009 13:34.
Abstract
Image registration methods play a crucial role in computational neuroanatomy. This paper mainly contributes to the field of image registration with the use of nonlinear spatial transformations. Particularly, problems connected to matching MRI brain image data obtained from various subjects and with various imaging conditions are solved here. Registration is driven by local forces derived from multimodal point similarity measures which are estimated with the use of joint intensity histogram and tissue probability maps. A spatial deformation model imitating principles of continuum mechanics is used. Five similarity measures are tested in an experiment with image data obtained from the Simulated Brain Database and a quantitative evaluation of the algorithm is presented. Results of application of the method in automated spatial detection of anatomical abnormalities in first-episode schizophrenia are presented.
Abstract (in Czech)
Článek přispívá zejméína do oblasti metod registrace medicínských obrazů s využitím nelineárních prostorových transformací. Řeší se zde problémy související s porovnávání multimodálních dat z MRI od různých subjektů. Registrace je řízena lokálními silami odvozenými z multimodální bodové podobnostní metriky, která je odhadnuta s využitím vzájmeného histogramu a tkáňových pravděpodobnostních map.
Links
MSM0021622404, plan (intention)Name: Vnitřní organizace a neurobiologické mechanismy funkčních systémů CNS
Investor: Ministry of Education, Youth and Sports of the CR, Research Intents
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