Metoda pružné registrace pro automatickou morfometrii obrazů mozku z MRI v neuropsychiatrickém výzkumu

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14110%2F07%3A00022048" target="_blank" >RIV/00216224:14110/07:00022048 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216305:26220/07:PU66940 RIV/65269705:_____/07:#0000387

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research

Popis výsledku v původním jazyce

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 imagedata 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.

Název v anglickém jazyce

A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research

Popis výsledku anglicky

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 imagedata 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.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

FH - Neurologie, neurochirurgie, neurovědy

OECD FORD obor

—

Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2007

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Transactions on Medical Imaging

ISSN

0278-0062

e-ISSN

—

Svazek periodika

26

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

452-461

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—