A Semi-automatic Approach for Segmentation of Three-Dimensional Microscopic Image Stacks of Cardiac Tissue

  • Thomas Seidel
  • Thomas Draebing
  • Gunnar Seemann
  • Frank B. Sachse
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7945)


The segmentation of three-dimensional microscopic images of cardiac tissues provides important parameters for characterizing cardiac diseases and modeling of tissue function. Segmenting these images is, however, challenging. Currently only time-consuming manual approaches have been developed for this purpose. Here, we introduce an efficient approach for the semi-automatic segmentation (SAS) of cardiomyocytes and the extracellular space in image stacks obtained from confocal microscopy. The approach is based on a morphological watershed algorithm and iterative creation of watershed seed points on a distance map. Results of SAS were consistent with results from manual segmentation (Dice similarity coefficient: 90.8±2.6%). Cell volume was 4.6±6.5% higher in SAS cells, which mainly resulted from cell branches and membrane protrusions neglected by manual segmentation. We suggest that the novel approach constitutes an important tool for characterizing normal and diseased cardiac tissues. Furthermore, the approach is capable of providing crucial parameters for modeling of tissue structure and function.


cardiac tissue confocal microscopy segmentation threedimensional algorithm 


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  1. 1.
    Lasher, R.A., Hitchcock, R.W., Sachse, F.B.: Towards modeling of cardiac micro-structure with catheter-based confocal microscopy: a novel approach for dye delivery and tissue characterization. IEEE Trans. Med. Imaging 28, 1156–1164 (2009)CrossRefGoogle Scholar
  2. 2.
    Lackey, D.P., Carruth, E.D., Lasher, R.A., Boenisch, J., Sachse, F.B., Hitchcock, R.W.: Three-dimensional modeling and quantitative analysis of gap junction distributions in cardiac tissue. Ann. Biomed. Eng. 39, 2683–2694 (2011)CrossRefGoogle Scholar
  3. 3.
    Lin, E., Hung, V.H., Kashihara, H., Dan, P., Tibbits, G.F.: Distribution patterns of the Na+-Ca2+ exchanger and caveolin-3 in developing rabbit cardiomyocytes. Cell Calcium 45, 369–383 (2009)CrossRefGoogle Scholar
  4. 4.
    Toure, A., Cabo, C.: Effect of heterogeneities in the cellular microstructure on propagation of the cardiac action potential. Med. Biol. Eng. Comput. 50, 813–825 (2012)CrossRefGoogle Scholar
  5. 5.
    Spach, M.S., Barr, R.C.: Effects of cardiac microstructure on propagating electrical waveforms. Circ. Res. 86, E23–E28 (2000)Google Scholar
  6. 6.
    Seidel, T., Salameh, A., Dhein, S.: A simulation study of cellular hypertrophy and connexin lateralization in cardiac tissue. Biophys. J. 99, 2821–2830 (2010)CrossRefGoogle Scholar
  7. 7.
    Cabo, C., Boyden, P.A.: Extracellular space attenuates the effect of gap junctional remodeling on wave propagation: a computational study. Biophys. J. 96, 3092–3101 (2009)CrossRefGoogle Scholar
  8. 8.
    Baum, J.R., Long, B., Cabo, C., Duffy, H.S.: Myofibroblasts cause heterogeneous Cx43 reduction and are unlikely to be coupled to myocytes in the healing canine infarct. Am. J. Physiol. Heart. Circ. Physiol. 302, H790–H800 (2012)CrossRefGoogle Scholar
  9. 9.
    Adiga, P.S.: Integrated approach for segmentation of 3-D confocal images of a tissue specimen. Microsc. Res. Tech. 54, 260–270 (2001)CrossRefGoogle Scholar
  10. 10.
    Hodneland, E., Bukoreshtliev, N.V., Eichler, T.W., Tai, X.C., Gurke, S., Lundervold, A., Gerdes, H.H.: A unified framework for automated 3-d segmentation of surface-stained living cells and a comprehensive segmentation evaluation. IEEE Trans. Med. Imaging 28, 720–738 (2009)CrossRefGoogle Scholar
  11. 11.
    Maes, F., Vandermeulen, D., Suetens, P., Marchal, G.: Computer-Aided Interactive Object Delineation Using an Intelligent Paintbrush Technique. In: Proceedings of the First International Conference on Computer Vision, Virtual Reality and Robotics in Medicine. Springer (1995)Google Scholar
  12. 12.
    Yoo, T.S., Ackerman, M.J., Lorensen, W.E., Schroeder, W., Chalana, V., Aylward, S., Metaxas, D., Whitaker, R.: Engineering and algorithm design for an image processing Api: A technical report on ITK–the Insight Toolkit. Stud. Health Technol. Inform. 85, 586–592 (2002)Google Scholar
  13. 13.
    Moré, J.: The Levenberg-Marquardt algorithm: Implementation and theory. In: Watson, G.A. (ed.) Numerical Analysis, vol. 630, pp. 105–116. Springer, Heidelberg (1978)CrossRefGoogle Scholar
  14. 14.
    Baere, R., Lehmann, G.: The watershed transform in ITK - discussion and new developments. The Insight Journal (2006)Google Scholar
  15. 15.
    Soille, P.: Morphological image analysis: principles and applications. Springer, Berlin (2003)Google Scholar
  16. 16.
    Bassien-Capsa, V., Fouron, J.C., Comte, B., Chorvatova, A.: Structural, functional and metabolic remodeling of rat left ventricular myocytes in normal and in sodium-supplemented pregnancy. Cardiovasc. Res. 69, 423–431 (2006)CrossRefGoogle Scholar
  17. 17.
    Gorelik, J., Yang, L.Q., Zhang, Y., Lab, M., Korchev, Y., Harding, S.E.: A novel Z-groove index characterizing myocardial surface structure. Cardiovasc. Res. 72, 422–429 (2006)CrossRefGoogle Scholar
  18. 18.
    Schwab, B.C., Seemann, G., Lasher, R.A., Torres, N.S., Wulfers, E.M., Arp, M., Carruth, E.D., Bridge, J.H., Sachse, F.B.: Quantitative Analysis of Cardiac Tissue Including Fibroblasts Using Three-Dimensional Confocal Microscopy and Image Reconstruction: Towards a Basis for Electrophysiological Modeling. IEEE Trans. Med. Imaging (epub., January 2013) Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Thomas Seidel
    • 1
  • Thomas Draebing
    • 1
  • Gunnar Seemann
    • 2
  • Frank B. Sachse
    • 1
    • 3
  1. 1.Nora Eccles Harrison Cardiovascular Research and Training InstituteUniversity of UtahSalt Lake CityUSA
  2. 2.Institute of Biomedical EngineeringKarlsruhe Institute of TechnologyKarlsruheGermany
  3. 3.Department of BioengineeringUniversity of UtahSalt Lake CityUSA

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