Multilevel block matching technique with the use of generalized partial volume interpolation for ...
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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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 | |
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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 |
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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) |
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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. |
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GP102/07/P263, research and development project | Name: Nelineární multimodální registrace pro automatickou morfometrii obrazů mozku z MRI založenou na anatomicky omezených prostorových deformacích |
Investor: Czech Science Foundation, Nonlinear multimodal registration for automatic morphometry of MRI brain images based on anatomically constrained spatial deformations | |
MSM0021622404, plan (intention) | Name: Vnitřní organizace a neurobiologické mechanismy funkčních systémů CNS |
Investor: Ministry of Education, Youth and Sports of the CR, The internal organisation and neurobiological mechanisms of functional CNS systems under normal and pathological conditions. |
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