Computer-aided infarction identification from cardiac CT images: A biomechanical approach with SVM

Ken C.L. Wong, Michael Tee, Marcus Chen, David A. Bluemke, Ronald M. Summers, Jianhua Yao

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

Abstract

Compared with global measurements such as ejection fraction, regional myocardial deformation can better aid detection of cardiac dysfunction. Although tagged and strain-encoded MR images can provide such regional information, they are uncommon in clinical routine. In contrast, cardiac CT images are more common with lower cost, but only provide motion of cardiac boundaries and additional constraints are required to obtain the myocardial strains. To verify the potential of contrast-enhanced CT images on computer-aided infarction identification, we propose a biomechanical approach combined with the support vector machine (SVM). A biomechanical model is used with deformable image registration to estimate 3D myocardial strains from CT images, and the regional strains and CT image intensities are input to the SVM classifier for regional infarction identification. Cross-validations on ten canine image sequences with artificially induced infarctions showed that the normalized radial and first principal strains were the most discriminative features, with respective classification accuracies of 87±13% and 84±10% when used with the normalized CT image intensity.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings
EditorsJoachim Hornegger, Alejandro F. Frangi, William M. Wells, Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, Nassir Navab, William M. Wells, William M. Wells, Alejandro F. Frangi, Joachim Hornegger, Nassir Navab
PublisherSpringer Verlag
Pages144-151
Number of pages8
ISBN (Print)9783319245706, 9783319245706, 9783319245706
DOIs
StatePublished - Jan 1 2015
Event18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
Duration: Oct 5 2015Oct 9 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9350
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
CountryGermany
CityMunich
Period10/5/1510/9/15

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Wong, K. C. L., Tee, M., Chen, M., Bluemke, D. A., Summers, R. M., & Yao, J. (2015). Computer-aided infarction identification from cardiac CT images: A biomechanical approach with SVM. In J. Hornegger, A. F. Frangi, W. M. Wells, A. F. Frangi, N. Navab, J. Hornegger, N. Navab, W. M. Wells, W. M. Wells, A. F. Frangi, J. Hornegger, & N. Navab (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings (pp. 144-151). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9350). Springer Verlag. https://doi.org/10.1007/978-3-319-24571-3_18