Development of Subject-Specific Geometric Spine Model through Use of Automated Active Contour Segmentation and Kinematic Constraint-Limited Registration
Identifieur interne : 001F18 ( Pmc/Checkpoint ); précédent : 001F17; suivant : 001F19Development of Subject-Specific Geometric Spine Model through Use of Automated Active Contour Segmentation and Kinematic Constraint-Limited Registration
Auteurs : Catherine G. Strickland [États-Unis] ; Daniel E. Aguiar [États-Unis] ; Eric A. Nauman [États-Unis] ; Thomas M. Talavage [États-Unis]Source :
- Journal of Digital Imaging [ 0897-1889 ] ; 2010.
Abstract
This paper describes the development of a patient-specific spine model through use of active contour segmentation and registration of intraoperative imaging of porcine vertebra augmented with kinematic constraints. The geometric active contours are fully automated and lead to a discrete representation of the image segmentation results. After determining errors within the segmentations, application of reliability theory allows the selection of active contour parameters to obtain best-fit segmentations from a stack of 2D images. The segmented images are then used in conjunction with C-arm fluoroscope images to simulate the result of intraoperative patient-specific model registration including patient and/or structure motion between preoperative and intraoperative scans. The results are validated through comparison of the error within the patient-specific model generated through use of the C-arm images with a model acquired directly from MRI images of the spine after motion. The results are applicable to the development of a wide variety of patient-specific geometric and biomechanical models.
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DOI: 10.1007/s10278-010-9336-z
PubMed: 20882395
PubMed Central: 3180553
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Aguiar</name><affiliation wicri:level="2"><nlm:aff id="Aff1">School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907-2035 USA</nlm:aff><country xml:lang="fr">États-Unis</country><placeName><region type="state">Indiana</region></placeName><wicri:cityArea>School of Electrical and Computer Engineering, Purdue University, West Lafayette</wicri:cityArea></affiliation></author><author><name sortKey="Nauman, Eric A" sort="Nauman, Eric A" uniqKey="Nauman E" first="Eric A." last="Nauman">Eric A. 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<front><journal-meta><journal-id journal-id-type="nlm-ta">J Digit Imaging</journal-id><journal-title-group><journal-title>Journal of Digital Imaging</journal-title></journal-title-group><issn pub-type="ppub">0897-1889</issn><issn pub-type="epub">1618-727X</issn><publisher><publisher-name>Springer-Verlag</publisher-name><publisher-loc>New York</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">20882395</article-id><article-id pub-id-type="pmc">3180553</article-id><article-id pub-id-type="publisher-id">9336</article-id><article-id pub-id-type="doi">10.1007/s10278-010-9336-z</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Development of Subject-Specific Geometric Spine Model through Use of Automated Active Contour Segmentation and Kinematic Constraint-Limited Registration</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Strickland</surname><given-names>Catherine G.</given-names></name><address><email>slatercg@purdue.edu</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Aguiar</surname><given-names>Daniel E.</given-names></name><address><email>daguiar@purdue.edu</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Nauman</surname><given-names>Eric A.</given-names></name><address><phone>+1-765-4948602</phone><fax>+1-765-4967537</fax><email>enauman@purdue.edu</email></address><xref ref-type="aff" rid="Aff2">2</xref><xref ref-type="aff" rid="Aff3">3</xref><xref ref-type="aff" rid="Aff4">4</xref></contrib><contrib contrib-type="author"><name><surname>Talavage</surname><given-names>Thomas M.</given-names></name><address><email>tmt@purdue.edu</email></address><xref ref-type="aff" rid="Aff1">1</xref><xref ref-type="aff" rid="Aff3">3</xref></contrib><aff id="Aff1"><label>1</label>School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907-2035 USA</aff><aff id="Aff2"><label>2</label>School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907-2088 USA</aff><aff id="Aff3"><label>3</label>Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907-2032 USA</aff><aff id="Aff4"><label>4</label>Department of Basic Medical Sciences, Purdue University, West Lafayette, IN 47907-2032 USA</aff></contrib-group><pub-date pub-type="epub"><day>30</day><month>9</month><year>2010</year></pub-date><pub-date pub-type="ppub"><month>10</month><year>2011</year></pub-date><volume>24</volume><issue>5</issue><fpage>926</fpage><lpage>942</lpage><permissions><copyright-statement>© Society for Imaging Informatics in Medicine 2010</copyright-statement></permissions><abstract id="Abs1"><p>This paper describes the development of a patient-specific spine model through use of active contour segmentation and registration of intraoperative imaging of porcine vertebra augmented with kinematic constraints. The geometric active contours are fully automated and lead to a discrete representation of the image segmentation results. After determining errors within the segmentations, application of reliability theory allows the selection of active contour parameters to obtain best-fit segmentations from a stack of 2D images. The segmented images are then used in conjunction with C-arm fluoroscope images to simulate the result of intraoperative patient-specific model registration including patient and/or structure motion between preoperative and intraoperative scans. The results are validated through comparison of the error within the patient-specific model generated through use of the C-arm images with a model acquired directly from MRI images of the spine after motion. The results are applicable to the development of a wide variety of patient-specific geometric and biomechanical models.</p></abstract><kwd-group><title>Key words</title><kwd>Segmentation</kwd><kwd>template geometry</kwd><kwd>patient-specific model</kwd><kwd>spine</kwd><kwd>active contour</kwd><kwd>fluoroscopy</kwd><kwd>kinematic constraints</kwd><kwd>imaging</kwd><kwd>image error</kwd><kwd>registration</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© Society for Imaging Informatics in Medicine 2011</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list><country><li>États-Unis</li></country><region><li>Indiana</li></region></list><tree><country name="États-Unis"><region name="Indiana"><name sortKey="Strickland, Catherine G" sort="Strickland, Catherine G" uniqKey="Strickland C" first="Catherine G." last="Strickland">Catherine G. Strickland</name></region><name sortKey="Aguiar, Daniel E" sort="Aguiar, Daniel E" uniqKey="Aguiar D" first="Daniel E." last="Aguiar">Daniel E. Aguiar</name><name sortKey="Nauman, Eric A" sort="Nauman, Eric A" uniqKey="Nauman E" first="Eric A." last="Nauman">Eric A. Nauman</name><name sortKey="Nauman, Eric A" sort="Nauman, Eric A" uniqKey="Nauman E" first="Eric A." last="Nauman">Eric A. Nauman</name><name sortKey="Nauman, Eric A" sort="Nauman, Eric A" uniqKey="Nauman E" first="Eric A." last="Nauman">Eric A. Nauman</name><name sortKey="Talavage, Thomas M" sort="Talavage, Thomas M" uniqKey="Talavage T" first="Thomas M." last="Talavage">Thomas M. Talavage</name><name sortKey="Talavage, Thomas M" sort="Talavage, Thomas M" uniqKey="Talavage T" first="Thomas M." last="Talavage">Thomas M. Talavage</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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