SCHWARZ, Daniel and Tomáš KAŠPÁREK. Multilevel block matching technique with the use of generalized partial volume interpolation for nonlinear intersubject registration of MRI brain images. In 16th European Signal Processing Conference EUSIPCO 2008. Lausanne: École Polytechnique Fédérale de Lausanne, 2008. p. 1-5.
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Basic information
Original name Multilevel block matching technique with the use of generalized partial volume interpolation for nonlinear intersubject registration of MRI brain images
Name in Czech Mnohoúrovňová technika srovnávání podobrazů s využitím zobecněné interpolace částečných objemů pro nelineární registraci obrazů mozku z MRI od různých subjektů
Authors SCHWARZ, Daniel and Tomáš KAŠPÁREK.
Edition Lausanne, 16th European Signal Processing Conference EUSIPCO 2008, p. 1-5, 5 pp. 2008.
Publisher École Polytechnique Fédérale de Lausanne
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 20200 2.2 Electrical engineering, Electronic engineering, Information engineering
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Organization unit Faculty of Medicine
Keywords in English image processing;image registration;interpolation
Tags image processing, image registration, interpolation
Tags International impact, Reviewed
Changed by Changed by: doc. Ing. Daniel Schwarz, Ph.D., učo 195581. Changed: 11. 9. 2008 07:33.
Abstract
Spatial normalization of MRI brain images by nonlinear image registration is an essential task for many applications in the field of computational neuroanatomy. Here, a multilevel block matching technique adapted to the problem of intersubject registration is presented. The concept of generalized partial volume (GPV) interpolation, which was originally used in joint intensity histogram computation, is used here in regional similarity matching. The influence of kernel function selected for GPV interpolation on the quality of registration is studied in experiments which include simulated brain images and synthetic deformations.
Abstract (in Czech)
Spatial normalization of MRI brain images by nonlinear image registration is an essential task for many applications in the field of computational neuroanatomy. Here, a multilevel block matching technique adapted to the problem of intersubject registration is presented. The concept of generalized partial volume (GPV) interpolation, which was originally used in joint intensity histogram computation, is used here in regional similarity matching. The influence of kernel function selected for GPV interpolation on the quality of registration is studied in experiments which include simulated brain images and synthetic deformations.
Links
GP102/07/P263, research and development projectName: Nelineární multimodální registrace pro automatickou morfometrii obrazů mozku z MRI založenou na anatomicky omezených prostorových deformacích
Investor: Czech Science Foundation, Postdoctoral projects
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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