Multilevel block matching technique with the use of generalized partial volume interpolation for nonlinear intersubject registration of MRI brain images

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.

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

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

Organization unit

Faculty of Medicine

Keywords in English

image processing;image registration;interpolation

Tags

image processing, image registration, interpolation

Tags

International impact, Reviewed

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Abstract

V originále

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.

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.

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Links

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.