Optimized Segmentation of Cellular Tomography through Organelles' Morphology and Image Features


  • Nur Intan Raihana Ruhaiyem Universiti Sains Malaysia, 11800 USM Penang, Malaysia.
  • Ahmad Sufril Azlan Mohamed Universiti Sains Malaysia, 11800 USM Penang, Malaysia.
  • Bahari Belaton Universiti Sains Malaysia, 11800 USM Penang, Malaysia.


Computational tracing of cellular images generally requires painstaking job in optimizing parameter(s). By incorporating prior knowledge about the organelle’s morphology and image features, the required number of parameter tweaking can be reduced substantially. In practical applications, however, the general organelles’ features are often known in advance, yet the actual organelles’ morphology is not elaborated. Two primary contributions of this paper are firstly the classification of insulin granules based on its image features and morphology for accurate segmentation – mainly focused at pre-processing image segmentation and secondly the new hybrid meshing quantification is presented. The method proposed in this study is validated on a set of manually defined ground truths. The study of insulin granules in particular; the location, and its image features has also opened up other options for future studies.


Olofsson, C. S., Salehi, A., Holm, C. & Rorsman, P.,“Palmitate Increases L-Type Ca2+ Currents and the Size of the Readily Releasable Granule Pool in Mouse Pancreatic Beta- Cells, ” Journal of Physiology, vol. 557, pp. 935-948, 2004.

Hutton, J. C.,“The Insulin Secretory Granule,” Diabetologia, vol. 32, pp. 271-281, 1989.

Howell, S. L., “The Molecular Organization of the Beta Granule of the Islets of Langerhans,” Advances in Cytopharmacology, vol. 2, pp. 319-327, 1974.

Ladinsky, M. S., Wu, C. C., Mcintosh, S., Mcintosh, J. R. & Howell, K. E., “ Structure of the Golgi and Distribution of Reporter Molecules at 20 degrees C Reveals the Complexity of the Exit Compartments,” Molecular Biology of the Cell, vol. 13, pp. 2810-2825, 2002.

Marsh, B. J., “Lessons from Tomographic Studies of the Mammalian Golgi,” Biochemical and Biophysics Acta, vol. 1744, pp. 273-292, 2005.

Russ, J. C. & Dehoff, R. T., “Practical Stereology,” New York, Kluwer Academic/Plenum, 2000.

Derganc, J., Mironov, A. A. & Svetina, S., “Physical Factors that Affect the Number and Size of Golgi Cisternae,” Traffic, vol. 7, pp. 85-96, 2006.

Griffiths, G., Fuller, S. D., Back, R., Hollinshead, M., Pfeiffer, S. & Simons, K., “The Dynamic Nature of the Golgi Complex,” Journal of Cell Biology, vol. 108, pp. 277-297, 1989.

Marsh, B. J., Mastronarde, D. N., Buttle, K. F., Howell, K. E. & Mcintosh, J. R., “Organellar Relationships in the Golgi Region of the Pancreatic Beta Cell Line, HIT T15, Visualized by High Resolution

Electron Tomography,” Proceedings of the National Academy of Science U S A, vol. 98, pp. 2399-406, 2001.

Ladinsky, M. S., Mastronarde, D. N., Mcintosh, J. R., Howell, K. E. & Staehelin, L. A., “Golgi Structure in Three Dimensions: Functional Insights From the Normal Rat Kidney Cell,” Journal of Cell Biology, vol. 144, pp. 1135-1149, 1999.

Nur Intan Raihana, R.,“Multiple, Object-oriented Segmentation Methods of Mammalian Cell Tomograms,” PhD Thesis, The University of Queensland, 2014.

Rorsman, P. & Renstrom, E., “Insulin Granule Dynamics in Pancreatic Beta Cells,” Diabetologia, vol. 46, pp. 1029-1045, 2003.

Noske, A. B., Costin, A. J., Morgan, G. P. & Marsh, B. J., “Expedited Approaches to Whole Cell Electron Tomography and Organelle Markup in situ in High-Pressure Frozen Pancreatic Islets,” Journal of Structural Biology, vol. 161, pp. 298-313, 2008.

Kremer, J. R., Mastronarde, D. N. & Mcintosh, J. R., “Computer Visualization of Three-Dimensional Image Data using IMOD,” Journal of Structural Biology, vol. 116, pp. 71-76, 1996.

Nur Intan Raihana, R.,“Semi-automated Cellular Tomogram Segmentation Workflow (CTSW): Towards an Automaic Target Scoring System,” The International Conference on Computer Graphics, Multimedia and Image Processing, 2014.




How to Cite

Ruhaiyem, N. I. R., Mohamed, A. S. A., & Belaton, B. (2016). Optimized Segmentation of Cellular Tomography through Organelles’ Morphology and Image Features. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(3), 79–83. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1006