Automated segmentation of a motion mask to preserve sliding motion in deformable registration of thoracic CT
Result description
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
Keywords
The result's identifiers
Result code in IS VaVaI
Result on the web
DOI - Digital Object Identifier
Alternative languages
Result language
angličtina
Original language name
Automated segmentation of a motion mask to preserve sliding motion in deformable registration of thoracic CT
Original language description
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
Czech name
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Czech description
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Classification
Type
Jx - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
GAP202/11/0111: Automatic analysis of light and electron microscopy neuronal data
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Medical Physics
ISSN
0094-2405
e-ISSN
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Volume of the periodical
39
Issue of the periodical within the volume
2
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
1006-1015
UT code for WoS article
000300215800046
EID of the result in the Scopus database
—
Result type
Jx - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP
JD - Use of computers, robotics and its application
Year of implementation
2012