Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
권호 표지
DOI QR코드

DOI QR Code

Analysis of Semantic Relations Between Multimodal Medical Images Based on Coronary Anatomy for Acute Myocardial Infarction

  • Park, Yeseul (Dept. of Electrical and Computer Engineering, Ajou University) ;
  • Lee, Meeyeon (Dept. of Electrical and Computer Engineering, Ajou University) ;
  • Kim, Myung-Hee (Dept. of Computer Science and Engineering, Ewha Womans University) ;
  • Lee, Jung-Won (Dept. of Electrical and Computer Engineering, Ajou University)
  • Received : 2015.07.07
  • Accepted : 2015.10.27
  • Published : 2016.03.31
Download PDF
⟨ Previous Next ⟩

Abstract

Acute myocardial infarction (AMI) is one of the three emergency diseases that require urgent diagnosis and treatment in the golden hour. It is important to identify the status of the coronary artery in AMI due to the nature of disease. Therefore, multi-modal medical images, which can effectively show the status of the coronary artery, have been widely used to diagnose AMI. However, the legacy system has provided multi-modal medical images with flat and unstructured data. It has a lack of semantic information between multi-modal images, which are distributed and stored individually. If we can see the status of the coronary artery all at once by integrating the core information extracted from multi-modal medical images, the time for diagnosis and treatment will be reduced. In this paper, we analyze semantic relations between multi-modal medical images based on coronary anatomy for AMI. First, we selected a coronary arteriogram, coronary angiography, and echocardiography as the representative medical images for AMI and extracted semantic features from them, respectively. We then analyzed the semantic relations between them and defined the convergence data model for AMI. As a result, we show that the data model can present core information from multi-modal medical images and enable to diagnose through the united view of AMI intuitively.

Keywords

References

  1. Z. Zhang, J. Fang, C. Gillespie, G. Wang, Y. Hong, and P. W. Yoon, "Age-specific gender differences in inhospital mortality by type of acute myocardial infarction," American Journal of Cardiology, vol. 109, no. 8, pp. 1097-1103, 2012. https://doi.org/10.1016/j.amjcard.2011.12.001
  2. M. A. Jabbar, P. Chandra, and B. I. Deekshatulu, "Cluster based association rule mining for heart attack prediction," Journal of Theoretical and Applied Information Technology, vol. 32, no. 2, pp. 196-201, 2011
  3. J. Spilka, V. Chudacek, J. Kuzilek, L. Lhotska and M. Hanuliak, "Detection of inferior myocardial infarction: a comparison of various decision systems and learning algorithms," Computing in Cardiology, vol. 37, pp. 273- 276, 2010.
  4. M. B. Messaoud, B. Khelil, and A. Kachouri, "Analysis and parameter extraction of P wave using correlation method," International Arab Journal of Information Technology, vol. 6, no. 1, pp. 40-46, 2009.
  5. D. Pal, C. Chakraborty, and K. M. Mandana, "Data mining approach for coronary artery disease screening," in Proceedings of 2011 International Conference on Image Information Processing (ICIP), Himachal Pradesh, India, 2011, pp. 1-6.
  6. H. Greenspan and A. T. Pinhas, "Medical image categorization and retrieval for PACS using the GMM-KL framework," IEEE Transactions on Information Technology in Biomedicine, vol. 11, no. 2, pp. 190-202, 2007. https://doi.org/10.1109/TITB.2006.874191
  7. Y. Tao, Z. Peng, A. Krishnan, and X. S. Zhou, "Robust learning-based parsing and annotation of medical radiographs," IEEE Transactions on Medical Imaging, vol. 30, no. 2, pp. 338-350, 2011. https://doi.org/10.1109/TMI.2010.2077740
  8. F. Valente, C. Viana-Ferreira, C. Costa, and J. L. Oliveira, "A RESTful image gateway for multiple medical image repositories," IEEE Transaction on Information Technology in Biomedicine, vol. 16, no. 3, pp. 356-364, 2012. https://doi.org/10.1109/TITB.2011.2176497
  9. L. R. Alvarez and S. Vargas Solis, "DICOM RIS/PACS telemedicine network implementation using free open source software," IEEE Latin America Transaction, vol. 11, no. 1, pp. 168-171, 2013. https://doi.org/10.1109/TLA.2013.6502797
  10. Carestream Health Inc., "DICOM Conformance Statement for the CARESTREAM Cardiology PACS," 2009; http://carestream.lv/cardiology-PACS_dicom_8H6985.pdf.
  11. P. Marcheschi, A. Ciregia, A. Mazzarisi, G. Augiero, and A. Gori, "A new approach to affordable and reliable cardiology PACS architecture using open-source technology," Computers in Cardiology, vol. 36, pp. 537-540, 2009.
  12. S. M. Lobodzinski, "Cardiac PACS: a digital system for real time cardiac image visualization and management," in Proceedings of 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Paris, France, 1992, pp. 2247-2248.
  13. U. Tachinardi, M. A. Gutierrez, L. Moura, B. Leao, C. Meneghetti, and C. P. Melo, "Integrating PACS and HIS in a nuclear cardiology department," Computers in Cardiology, vol. 20, pp. 819-822, 1993.
  14. M. F. Santarelli, V. Positano, P. Marcheschi, L. Landini, P. Marzullo, and A. Benassi, "Multimodal cardiac image fusion by geometric features registration and warping," Computers in Cardiology, vol. 28, pp. 277-280, 2001.
  15. G. Kiss, J. P. Asen, J. Bogaert, B. Amundsen, P. Claus, J. D'hooge, and H. G. Torp, "Multi-modal cardiac image fusion and visualization on the GPU," in Proceedings of IEEE International Ultrasonic Symposium (IUS), Orlando, FL, 2011, pp. 254-257.
  16. Y. Chenoune, Y. Bouaounce, E. Delechelle, E. Petit, J. Garot, and A. Rahmouni, "MR/CT multimodal registration of short-axis slices in CT volumes," in Proceedings of 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Orlando, FL, 2007, pp. 4496-4499.
  17. INFINITT Cardiology PACS [Online]. Available: http://www.infinitt.com/cms/index.
  18. Y. Igarashi, T. Igarashi, R. Haraguchi, and K. Nakazawa, "Generating graphical reports on cardiac catheterization," in Artery Bypass. Rijeka, Croatia: InTech, 2013, pp. 367-384.
  19. S. Mhiri, S. Despres, and E. Zagrouba, "Ontologies for the semantic-based medical image indexing an overview," in Proceedings of the 2008 International Conference on Information & Knowledge Engineering (IKE2008), Las Vegas, NV, 2008, pp. 311-317.
  20. D. K. Iakovidis, D. Schober, M. Boeker, and S. Schulz, "An ontology of image representations for medical image mining", in Proceedings of 9th International Conference on Information Technology and Applications in Biomedicine (ITAB2009), Larnaca, Cyprus, 2009, pp. 1-4.
  21. D. L. Rubin, "Finding the meaning in images: annotation and image markup," Philosophy, Psychiatry, & Psychology, vol. 18, no. 4, pp. 311-318, 2011. https://doi.org/10.1353/ppp.2011.0045
  22. S. Gedzelman, M. Simonet, D. Bernhard, G. Diallo, and P. Palmer, "Building an ontology of cardio-vascular diseases for concept-based information retrieval," Computers in Cardiology, vol. 32, pp. 255-258, 2005.
  23. C. De Maio, G. Fenza, V. Loia, and M. Parente, "Biomedical data integration and ontology-driven multi-facets visualization," in Proceedings of International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, 2015, pp. 1-8.
  24. J. T. Dodge, B. G. Brown, E. L. Bolson, and H. T. Dodge, "Lumen diameter of normal human coronary arteries: influence of age, sex, anatomic variation, and left ventricular hypertrophy or dilation," Circulation, vol. 85, no. 1, pp. 232-246, 1992.
  25. L. M. Zir, S. W. Miller, R. D. Dinsmore, J. P. Gilbert, and J. W. Harthorne, "Interobserver variability in coronary angiography," Circulation, vol. 53, no. 4, pp. 627-632, 1976. https://doi.org/10.1161/01.CIR.53.4.627
  26. J. G. Murphy and M. A. Lloyd, Mayo Clinic Cardiology: Concise Textbook, 4th ed. New York, NY: Oxford University Press, 2013.
  27. J. T. Ortiz-Perez, J. Rodriguez, S. N. Meyers, D. C. Lee, C. Davidson, and E. Wu, "Correspondence between the 17-segment model and coronary arterial anatomy using contrast-enhanced cardiac magnetic resonance imaging," JACC: Cardiovascular Imaging, vol. 1, no. 3, pp. 282-293, 2008. https://doi.org/10.1016/j.jcmg.2008.01.014
  28. W. L. Henry, A. DeMaria, R. Gramiak, D. L. King, J. A. Kisslo, R. L. Popp, et al., "Report of the American Society of Echocardiography Committee on nomenclature and standards in two-dimensional echocardiography," Circulation, vol. 62, no. 8, pp. 212-217, 1980. https://doi.org/10.1161/01.CIR.62.2.212
  29. R. M. Lang, M. Bierig, R. B. Devereux, F. A. Flachskampf, E. Foster, P. A. Pellikka, et al., "Recommendations for chamber quantification," European Heart Journal: Cardiovascular Imaging, vol. 7, no. 2, pp. 79-108, 2006.
  30. M. D. Cerqueira, N. J. Weissman, V. Dilsizian, A. K. Jacobs, S. Kaul, W. K. Laskey, et al., "Standardized myocardial segmentation and nomenclature for tomographic imaging of the heart," Journal of Cardiovascular Magnetic Resonance, vol. 4, no. 2, pp. 203-210, 2002. https://doi.org/10.1081/JCMR-120003946