Unifying vascular information in intensity-based nonrigid lung CT registration

Kunlin Cao, Kai Ding, Gary E. Christensen, Madhavan L. Raghavan, Ryan E. Amelon, Joseph M. Reinhardt

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Image registration plays an important role within pulmonary image analysis. Accurate registration is critical to post-analysis of lung mechanical properties. To improve registration accuracy, we utilize the rich information of vessel locations and shapes, and introduce a new similarity criterion, sum of squared vesselness measure difference (SSVMD). This metric is added to three existing intensity-based similarity criteria for nonrigid lung CT image registration to show its ability in improving matching accuracy. The registration accuracy is assessed by landmark error calculation and distance map visualization on vascular tree. The average landmark errors are reduced by over 20% and are within 0.7 mm after adding SSVMD constraint to three existing intensity-based similarity metrics. Visual inspection shows matching accuracy improvements in the lung regions near the thoracic cage and near the diaphragm. Experiments also show this vesselness constraint makes the Jacobian map of transformations physiologically more plausible and reliable.

Original languageEnglish (US)
Title of host publicationBiomedical Image Registration - 4th International Workshop, WBIR 2010, Proceedings
Pages1-12
Number of pages12
DOIs
StatePublished - Aug 12 2010
Externally publishedYes
Event4th International Workshop on Biomedical Image Registration, WBIR 2010 - Lubeck, Germany
Duration: Jul 11 2010Jul 13 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6204 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Workshop on Biomedical Image Registration, WBIR 2010
CountryGermany
CityLubeck
Period7/11/107/13/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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