Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2010-12-14
pubmed:abstractText
The goal of this study is to develop a matching algorithm that can handle large geometric changes in x-ray computed tomography (CT)-derived lung geometry occurring during deep breath maneuvers. These geometric relationships are further utilized to build a dynamic lung airway model for computational fluid dynamics (CFD) studies of pulmonary air flow. The proposed algorithm is based on a cubic B-spline-based hybrid registration framework that incorporates anatomic landmark information with intensity patterns. A sequence of invertible B-splines is composed in a multiresolution framework to ensure local invertibility of the large deformation transformation and a physiologically meaningful similarity measure is adopted to compensate for changes in voxel intensity due to inflation. Registrations are performed using the proposed approach to match six pairs of 3D CT human lung datasets. Results show that the proposed approach has the ability to match the intensity pattern and the anatomical landmarks, and ensure local invertibility for large deformation transformations. Statistical results also show that the proposed hybrid approach yields significantly improved results as compared with approaches using either landmarks or intensity alone.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-10534053, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-11437112, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-12071616, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-12643552, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-12946468, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-15587645, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-15896996, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-16467578, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-16503382, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-16878564, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-17360247, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-17498570, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-17654918, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-17924721, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-18072476, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-18270067, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-18334448, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-18404936, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-18501665, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-19171516, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-19175115, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-19265208, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-19457731, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-19482288, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-19810495, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-20009196, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-20162357, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-20384264, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-20483412, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-20614248, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-21105146, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-4030599, http://linkedlifedata.com/resource/pubmed/commentcorrection/21149947-9184894
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1361-6560
pubmed:author
pubmed:issnType
Electronic
pubmed:day
7
pubmed:volume
56
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
203-18
pubmed:dateRevised
2011-9-26
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
A cubic B-spline-based hybrid registration of lung CT images for a dynamic airway geometric model with large deformation.
pubmed:affiliation
Department of Mechanical and Industrial Engineering, University of Iowa, Iowa City, IA 52242, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural