Automated segmentation of a motion mask to preserve sliding motion in deformable registration of thoracic CT

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00193281" target="_blank" >RIV/68407700:21230/12:00193281 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1118/1.3679009" target="_blank" >http://dx.doi.org/10.1118/1.3679009</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1118/1.3679009" target="_blank" >10.1118/1.3679009</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automated segmentation of a motion mask to preserve sliding motion in deformable registration of thoracic CT

Popis výsledku v původním jazyce

Deformable registration generally relies on the assumption that the sought spatial transformation is smooth. Breathing motion involves sliding motion of the lung with respect to the chest wall. In the case of sliding motion, a discontinuity is present inthe motion field and the smoothness assumption can lead to poor matching accuracy. Many authors have proposed alternative registration methods to preserve sliding motion, several of which rely on prior segmentations. We focus on a particular, subanatomical segmentation, called a motion mask, because it is advanta- geous for subsequent registration. The motion mask separates moving from less-moving regions, conveniently allowing to simultaneously estimate the motion for similarly moving tissue. We propose an original method for automatically extracting a motion mask from a CT image of the thorax. The obtained segmentation is useful for any registration method relying on a prior segmentation to account for sliding motion. The method is b

Název v anglickém jazyce

Automated segmentation of a motion mask to preserve sliding motion in deformable registration of thoracic CT

Popis výsledku anglicky

Deformable registration generally relies on the assumption that the sought spatial transformation is smooth. Breathing motion involves sliding motion of the lung with respect to the chest wall. In the case of sliding motion, a discontinuity is present inthe motion field and the smoothness assumption can lead to poor matching accuracy. Many authors have proposed alternative registration methods to preserve sliding motion, several of which rely on prior segmentations. We focus on a particular, subanatomical segmentation, called a motion mask, because it is advanta- geous for subsequent registration. The motion mask separates moving from less-moving regions, conveniently allowing to simultaneously estimate the motion for similarly moving tissue. We propose an original method for automatically extracting a motion mask from a CT image of the thorax. The obtained segmentation is useful for any registration method relying on a prior segmentation to account for sliding motion. The method is b

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/GAP202%2F11%2F0111" target="_blank" >GAP202/11/0111: Automatická analýza obrazů nervové tkáně ze světelné a elektronové mikroskopie</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Medical Physics

ISSN

0094-2405

e-ISSN

—

Svazek periodika

39

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

10

Strana od-do

1006-1015

Kód UT WoS článku

000300215800046

EID výsledku v databázi Scopus

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