Fast reconstruction of image deformation field using radial basis function

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00097217" target="_blank" >RIV/00216224:14330/17:00097217 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/7950719/" target="_blank" >http://ieeexplore.ieee.org/document/7950719/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ISBI.2017.7950719" target="_blank" >10.1109/ISBI.2017.7950719</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fast reconstruction of image deformation field using radial basis function

Popis výsledku v původním jazyce

Fast and accurate registration of image data is a key component of computer-aided medical image analysis. Instead of performing the registration directly on the input images, many algorithms compute the transformation using a sparse representation extracted from the original data. However, in order to apply the resulting transformation onto the original images, a dense deformation field has to be reconstructed using a suitable inter-/extra-polation technique. In this paper, we employ the radial basis function (RBF) to reconstruct the dense deformation field from a sparse transformation computed by a model-based registration. Various kernels are tested using different scenario. The dense deformation field is used to warp the source image and compare it quantitatively to the target image using two different metrics. Moreover, the influence of the number and distribution of the control points required by the RBF is studied via two different scenarios. Beside the accuracy, the performance of the method accelerated using a GPU is reported.

Název v anglickém jazyce

Fast reconstruction of image deformation field using radial basis function

Popis výsledku anglicky

Fast and accurate registration of image data is a key component of computer-aided medical image analysis. Instead of performing the registration directly on the input images, many algorithms compute the transformation using a sparse representation extracted from the original data. However, in order to apply the resulting transformation onto the original images, a dense deformation field has to be reconstructed using a suitable inter-/extra-polation technique. In this paper, we employ the radial basis function (RBF) to reconstruct the dense deformation field from a sparse transformation computed by a model-based registration. Various kernels are tested using different scenario. The dense deformation field is used to warp the source image and compare it quantitatively to the target image using two different metrics. Moreover, the influence of the number and distribution of the control points required by the RBF is studied via two different scenarios. Beside the accuracy, the performance of the method accelerated using a GPU is reported.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI)

ISBN

9781509011711

ISSN

1945-7928

e-ISSN

—

Počet stran výsledku

5

Strana od-do

1146-1150

Název nakladatele

IEEE

Místo vydání

Neuveden

Místo konání akce

Melbourne, VIC, Australia

Datum konání akce

18. 4. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000414283200265