Elastic Registration of Biomedical Images on CUDA-Supported Graphics Processor Units

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F10%3A00168767" target="_blank" >RIV/68407700:21460/10:00168767 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Elastic Registration of Biomedical Images on CUDA-Supported Graphics Processor Units

Popis výsledku v původním jazyce

Elastic registration is a task of finding the matching of two images, using geometric and elastic transformations, so that objects in images have the same size, position and orientation. We apply elastic registration in the framework of volume reconstruction, where an object acquired from parallel physical sections is composed and mutual positions of the sections including deformations caused by their cutting have to be found. The method lies in optimizing a functional consisting of two parts: first, discrete total variation as a measure of roughness and, second, L1 norm as a measure of dissimilarity of images. As a parallelizable optimization strategy we apply a potential-based equivalent transformation of a (max,+)-labelling problem. CUDA-based implementation of the described elastic registration algorithm is reasonably fast, requires seconds to minutes of calculations, provides good results and, thus, can be used for practical tasks dealing with alignment of biomedical images.

Název v anglickém jazyce

Elastic Registration of Biomedical Images on CUDA-Supported Graphics Processor Units

Popis výsledku anglicky

Elastic registration is a task of finding the matching of two images, using geometric and elastic transformations, so that objects in images have the same size, position and orientation. We apply elastic registration in the framework of volume reconstruction, where an object acquired from parallel physical sections is composed and mutual positions of the sections including deformations caused by their cutting have to be found. The method lies in optimizing a functional consisting of two parts: first, discrete total variation as a measure of roughness and, second, L1 norm as a measure of dissimilarity of images. As a parallelizable optimization strategy we apply a potential-based equivalent transformation of a (max,+)-labelling problem. CUDA-based implementation of the described elastic registration algorithm is reasonably fast, requires seconds to minutes of calculations, provides good results and, thus, can be used for practical tasks dealing with alignment of biomedical images.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2010

Kód důvěrnosti údajů

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

Název statě ve sborníku

Analysis of Biomedical Signals and Images, BIOSIGNAL 2010, Proceedings

ISBN

978-80-214-4106-4

ISSN

1211-412X

e-ISSN

—

Počet stran výsledku

6

Strana od-do

—

Název nakladatele

Brno University of Technology

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

27. 6. 2010

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—