Segmentation of Moving Cells in Bright Field and Epi-Fluorescent Microscopic Image Sequences

1. Iwanowski, M., Korzyńska, A.: Detection of the area covered by neural stem cells in cultures using textural segmentation and morphological watershed. In: ASC; Computer Recognition Systems, vol. 3, pp. 543–557. Springer, Heidelberg (2009)

   Chapter  Google Scholar 

2. Tse, S., Bradbury, L., Wan, J.W.L., Djambazian, H., Sladek, R., Hudson, T.: A combined watershed and level set method for segmentation of brightfield cell images. In: Proceedings of the SPIE, vol. 7258, pp. 72593G–72593G-10 (2009)

   Google Scholar 

3. Iwanowski, M.: Metody morfologiczne w przetwarzaniu obraz”ow cyfrowych, AOW EXIT (2009)

   Google Scholar 

4. Korzyńska, A., Iwanowski, M., Neuman, U., Dobrowolska, E., Hoser, P.: Comparison of the methods of microscopic image segmentation. In: Dossel, S. (ed.) WC 2009, IFMBE Proceedings, vol. 25/IV, pp. 425–428 (2009) ISBN 978-3-642-03897-6 (book), ISSN 1680-0737 (CD)

   Google Scholar 

5. Selinummi, J., Ruusuvuori, P., Podolsky, I., Ozinsky, A., Gold, E., Yli-Harja, O., Aderem, A., Shmulevich, I.: Bright Field Microscopy as an Alternative to Whole Cell Fluorescence in Automated Analysis of Macrophage Images. PLoS ONE 4(10), e7497 (2009)

   Google Scholar 

6. Ramoser, H.: Leukocyte segmentation and SVM classification in blood smear images. Machine Graphics and Vision 17(1/2), 187–200 (2008)

   Google Scholar 

7. Piętka, B.D., Dulewicz, A., Jaszczak P.: Removing artefacts from microscopic Images of cytological smears. Machine Graphics and Vision 17(1/2),131–152 (2008)

   Google Scholar 

8. Korzyńska, A., Zdunczuk, M.: Clustering as a method of image simplification. In: Pietka, K. (ed.) Inform. Tech. in Biomed., ASC, vol. 47, pp. 365–376 (2008)

   Google Scholar 

9. Marciniak, A., Nieczkowski, T., Obuchowicz, A.: Color Homogram for segmentation of fine needle biopsy images. Machine Graphics and Vision 17(1/2), 153–165 (2008)

   Google Scholar 

10. Witkowski, L.: A computer system for cells motility Evaluation. Machine Graphics and Vision 17(1/2), 167–186 (2008)

    Google Scholar 

11. Markiewcz, T., Osowski, S.: Morphological operations for blood cells extraction from the image of the bone marrow smear. Przeglad Elektrotechniczny 84(5), 24–26 (2008)

    Google Scholar 

12. Korzyńska, A., Iwanowski, M.: Detection of mitotic cell fraction in stem cells in cultures. In: ASC; Information Technologies in Biomedicine 1, vol. 47, pp. 365–376. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

13. Korzyńska, A., Strojny, W., Hoppe, A., Wertheim, D., Hoser, P.: Segmentation of microscope images of living cells. Pattern Anal Applic. 10, 301–319 (2007)

    Article  Google Scholar 

14. Buzanska, L., Jurga, M., Stachowiak, E.K., Stachowiak, M.K., Domanska-Janik, K.: Neural Stem-like Cell Line Derived from a Nonhematopoietic Population of Human Umbilical Cord Blood. Stem Cell and Development 15, 391–406 (2006)

    Article  Google Scholar 

15. Boier Marti, I.M., Martineus, D.C.: Identification of spherical virus particles in digitized images of entire electron micrographs. Journal of Structural Biology 120, 146–157 (2005)

    Article  Google Scholar 

16. Koprowski, R., Wr”oblewski, Z.: Automatic segmentation of biological cell structures based on conditional opening and closing. Machine Graphics and Vision 14, 285–307 (2005)

    Google Scholar 

17. Sabino, D.M.D., da F Costa, F., Costa, L., Rizzatti, E.G., Zago, M.A.: A texture approach to leukocyte recognition. Real-Time Imaging 10(4), 205–216 (2004)

    Article  Google Scholar 

18. Soille, P.: Morphological Image Analysis: Principles and Applications. Springer, Heidelberg (2004)

    Google Scholar 

19. Jiang, K., Liao, Q.M., Dai, S.Y.: A novel white blood cell segmentation scheme using scale-space altering and watershed clustering. In: Proc. Int. Conf. on Machine Learning and Cybernetics, vol. 5, pp. 2820–2825 (2003)

    Google Scholar 

20. Buzanska, L., Machaj, E.K., Zablocka, B.: Human Cord Blood - Derived Cells Attain Neuronal and Glial Features in Vitro. J. Cell Sci. 115, 2131–2138 (2002)

    Google Scholar 

21. Periasamy, A.: Methods in Cellular Imaging. Oxford University Press, Oxford (2001)

    Google Scholar 

22. Comaniciu, D., Meer, P.: Cell image segmentation for diagnostic pathology. In: Advanced Algorithmic Approaches to Medical Image Segmentation: State-of-the-Art Application in Cardiology, Neurology, Mammography and Pathology, pp. 541–558 (2001)

    Google Scholar 

23. Iwanowski, M., Serra, J.: The morphological-affine object deformation. In: Mathematical Morphology and its Applications to Signal and Image Processing, pp. 81–90. Kluwer Academic Publishers, Dordrecht (2000)

    Google Scholar 

24. Pham, D.L., Xu, C., Prince, J.L.: A survey of current methods in medical image segmentation, Vol. 2, pp. 315–338 (2000)

    Google Scholar 

25. Serra, J.: Hausdorff distance and interpolations. In: Mathematical morphology and its Applications to Image and Signal Processing, pp. 107–114. Kluwer Academic Publishers, Dordrecht (1998)

    Google Scholar 

26. Meyer, F.: A morphological interpolation method for mosaic images. In: Mathematical Morphology and its Applications to Image and Signal Processing, pp. 337–344. Kluwer Academic Publishers, Dordrecht (1996)

    Google Scholar 

27. Serra, J.: Image analysis and mathematical morphology, vol. 1. Academic Press, London (1983)

    Google Scholar 

28. Fu, K.S., Mui, J.K.: A survey on image segmentation. Pattern Recognition 13(1), 3–16 (1981)

    Article  MathSciNet  Google Scholar 

Download references