Three-dimensional segmentation of bones from CT and MRI using fast level sets

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Three-dimensional segmentation of bones from CT and MRI using fast level sets

Popis výsledku v původním jazyce

Our task is to segment bones from 3D CT and MRI images. The main application is creation of 3D mesh models for finite element modeling. These surface and volume vector models can be used for further biomechanical processing and analysis. We selected a novel fast level set method because of its high computational efficiency, while preserving all advantages of traditional level set methods. Unlike in traditional level set methods, we are not solving partial differential equations (PDEs). Instead, the contours are represeted by two sets of points, corresponding to the inner and outer edge of the object boundary. We have extended the original implementation in 3D, where the speed advantage over classical level set segmentation are even more pronounced. Wecan segment a CT image of 512x512x125 in less than 20s by this method. It is approximately two orders of magnitude faster than standard narrow band algorithms. Our experiments with real 3D CT and MRI images presented in this paper showed

Název v anglickém jazyce

Three-dimensional segmentation of bones from CT and MRI using fast level sets

Popis výsledku anglicky

Our task is to segment bones from 3D CT and MRI images. The main application is creation of 3D mesh models for finite element modeling. These surface and volume vector models can be used for further biomechanical processing and analysis. We selected a novel fast level set method because of its high computational efficiency, while preserving all advantages of traditional level set methods. Unlike in traditional level set methods, we are not solving partial differential equations (PDEs). Instead, the contours are represeted by two sets of points, corresponding to the inner and outer edge of the object boundary. We have extended the original implementation in 3D, where the speed advantage over classical level set segmentation are even more pronounced. Wecan segment a CT image of 512x512x125 in less than 20s by this method. It is approximately two orders of magnitude faster than standard narrow band algorithms. Our experiments with real 3D CT and MRI images presented in this paper showed

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2008

Kód důvěrnosti údajů

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

Název statě ve sborníku

SPIE MI 2008: Proceedings of the SPIE Medical Imaging 2008 Conference

ISBN

978-0-8194-7098-0

ISSN

0277-786X

e-ISSN

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Počet stran výsledku

10

Strana od-do

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Název nakladatele

SPIE

Místo vydání

Washington

Místo konání akce

San Diego

Datum konání akce

16. 2. 2008

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000256058600144