Advertisement

Shape Analysis of the Left Ventricular Endocardial Surface and Its Application in Detecting Coronary Artery Disease

  • Anirban Mukhopadhyay
  • Zhen Qian
  • Suchendra Bhandarkar
  • Tianming Liu
  • Szilard Voros
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6666)

Abstract

Coronary artery disease is the leading cause of morbidity and mortality worldwide. The complex morphological structure of the ventricular endocardial surface has not yet been studied properly due to the limitations of conventional imaging techniques. With the recent developments in Multi-Detector Computed Tomography (MDCT) scanner technology, we propose to study, in this paper, the complex endocardial surface morphology of the left ventricle via analysis of Computed Tomography (CT) image data obtained from a 320 Multi-Detector CT scanner. The CT image data is analyzed using a 3D shape analysis approach and the clinical significance of the analysis in detecting coronary artery disease is investigated. Global and local 3D shape descriptors are adapted for the purpose of shape analysis of the left ventricular endocardial surface. In order to study the association between the incidence of coronary artery disease and the alteration of the endocardial surface structure, we present the results of our shape analysis approach on 5 normal data sets, and 6 abnormal data sets with obstructive coronary artery disease. Based on the morphological characteristics of the endocardial surface as quantified by the shape descriptors, we implement a Linear Discrimination Analysis (LDA)-based classification algorithm to test the effectiveness of our shape analysis approach. Experiments performed on a strict leave-one-out basis are shown to achieve a classification accuracy of 81.8%.

Keywords

Ventricular endocardial surface cardiovascular CT shape analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Goo, S., Joshi, P., Sand, G., Gerneke, D., Taberner, A., Dollie, Q., LeGrice, I., Loiselle, D.: Trabeculae Carneae as Models of the Ventricular Walls: Implications for the Delivery of Oxygen. Jour. Gen. Physiology 134(4), 339–350 (2009)CrossRefGoogle Scholar
  2. 2.
    Agmon, Y., Connoll, H.M., Olson, L.J., Khandheria, B.K., Seward, J.B.: Noncompaction of the Ventricular Myocardium. Jour. Amer. Soc. Echocardiography 12(10), 859–863 (1999)CrossRefGoogle Scholar
  3. 3.
    Chen, T., Metaxas, D.N., Axel, L.: 3D Cardiac Anatomy Reconstruction Using High Resolution CT Data. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004. LNCS, vol. 3216, pp. 411–418. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Axel, L.: Papillary Muscles Do Not Attach Directly to the Solid Heart Wall. Circulation 109, 3145–3148 (2004)CrossRefGoogle Scholar
  5. 5.
    Cerqueira, M.D., Weissman, N.J., Dilsizian, V., Jacobs, A.K., Kaul, S., Laskey, W.K., et al.: Standardized Myocardial Segmentation and Nomenclature for Tomographic Imaging of the Heart. Circulation 105, 539–542 (2002)CrossRefGoogle Scholar
  6. 6.
    Osada, R., Funkhouser, T., Chazelle, B., Dobkin, D.: Shape Distributions. ACM Trans. Graphics 21(4), 807–832 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Koenderink, J.: Solid Shape. The MIT Press, Cambridge (1990)Google Scholar
  8. 8.
    Zaharia, T., Preteux, F.: 3D Shape-based Retrieval Within the MPEG-7 Framework. In: Proc. SPIE Conf. Nonlinear Image Processing and Pattern Analysis XII, vol. 4304, pp. 133–145 (2001)Google Scholar
  9. 9.
    Li, C., Xu, C., Gui, C., Fox, M.D.: Level Set Evolution Without Re-initialization: A New Variational Formulation. In: Proc. IEEE Conf. CVPR 2005, vol. 1, pp. 430–436 (2005)Google Scholar
  10. 10.
    Medtronic Inc. The Visible Heart webpage, http://www.visibleheart.com/index.shtml
  11. 11.
    Martinez, A.M., Kak, A.C.: PCA versus LDA. IEEE Trans. Pattern Analysis and Machine Intelligence 23(2), 228–233 (2001)CrossRefGoogle Scholar
  12. 12.
    Zhang, Y., Hamza, A.B.: Vertex-based Diffusion for 3-D Mesh Denoising. IEEE Trans. Image Processing 16(4), 1036–1045 (2007)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Anirban Mukhopadhyay
    • 1
  • Zhen Qian
    • 2
  • Suchendra Bhandarkar
    • 1
  • Tianming Liu
    • 1
  • Szilard Voros
    • 2
  1. 1.Department of Computer ScienceThe University of GeorgiaAthensUSA
  2. 2.Piedmont Heart InstituteAtlantaUSA

Personalised recommendations