Abstract
Nuclear morphology abnormalities in cells are often the symptom of the cell death. However, minor disturbances in nuclear shape, such as a slight blebbing or deformation, may indicate characteristic medical disorders or therapeutic effect. The analysis of microscopic images requires time consuming observations and meticulous analysis that often are encumbered with human mistake. In the present work, image analysis of nuclei as a method of morphological verification is presented. The automated analysis of numerous cellular nuclei images may be a useful tool for any biological or analytical laboratory.
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References
Fulda, S., Gorman, A.M., Hori, O., Samali, A.: Cellular stress responses: cell survival and death. J. Cell Biol. 12, 23–46 (2010)
Nafe, R., Franz, K., Shlote, W., Shneider, B.: Morphology of tumor cell nuclei is significantly related with survival time of patients with glioblastomas. Clin. Cancer Res. 11(6), 2141–2148 (2005)
Misteli, T.: Beyond the sequence: cellular organization of genome function. Cell 128, 787–800 (2007)
Dey, P.: Cancer nucleus: morphology and beyond. Dignostic Cytopathol. 38(5), 1–23 (2010)
Bignold, L.P.: The mutator phenotype theory of carcinogenesis and the complex histopathology of tumours: support for the theory from the independent occurrence of nuclear abnormality, loss of specialization and invasiveness among occasional neoplastic lesions. Cell Mol. Life Sci. 60, 883–891 (2003)
Smith, T.F., Waterman, M.S.: Identification of common molecular subsequences. J. Mol. Biol. 147, 195–197 (1981)
Sapierzyski, R.: Rokowanie u pacjentw onkologicznych. Badania morfologiczne. ycie weterynaryjne 84, 723–726 (2009)
Jogai, S., Jassar, A., Adisena, A., Dey, P.: Fine needle aspiration cytology of thyroid lesions. Acta Cytol. 49, 483–488 (2005)
Rajesh, L., Dey, P., Joshi, K.: Fine needle aspiration cytology of lobular carcinoma: comparison with other breast lesions. Acta Cytol. 47, 177–182 (2003)
Krysko, D.V., Vanden, B.T., D’Herde, K., Vandenabeele, P.: Apoptosis and necrosis: detection, discrimination and phagocytosis. Methods 44(3), 205–221 (2008)
Elmore, S.: Apoptosis: a review of rogrammed cell death. Toxicol Pathol. 35(4), 495–516 (2007)
Webster, M., Witkin, K.L., Fix, O.C.: Sizing up the nucleus: nuclear shape, size and nuclear-envelope assembly. J. Cell Sci. 122, 1477–1486 (2009)
Ziegler, U., Groscurth, P.: Morphological features of cell death. News Physiol. Sci. 19, 124–128 (2004)
Schöchlin, M., Weissinger, S.E., Brandes, A.R., Herrmann, M., Mller, P., Lennerz, J.K.: A nuclear circularity-based classifier for diagnostic distinction of desmoplastic from spindle cell melanoma in digitized histological images. J. Pathol. Inform. 5, 40 (2014)
Driscoll, M.K., Albanese, J.L., Xiong, Z.M., Mailman, M., Losert, W., Cao, K.: Automated image analysis of nuclear shape: What can we learn from a prematurely aged cell? Aging 4(2), 119–132 (2012)
Dvir, L., Nissim, R., Alvarez-Elizondo, M.B., Weihs, D.: Quantitative measures to reveal coordinated cytoskeleton-nucleus reorganization during in vitro invasion of cancer cells. New J. Phys. 17, 043010 (2015)
Agley, C.C., Velloso, C.P., Lazarus, N.R., Harridge, S.D.R.: An image analysis method for the precise selection and quantitation of fluorescently labeled cellular constituents: application to the measurement of human muscle cells in culture. J. Histochem. Cytochem. 60(6), 428–438 (2012)
Costa, L.F., Cesar Jr., R.M.: Shape Analysis and Classification: Theory and Practice. CRC Press, Boca Raton (2009)
Freeman, H., Davis, L.: A corner-finding algorithm for chain-coded curves. IEEE Trans. Comp. C–26, 297–303 (1977)
Shawe-Taylor, J., Cristianini, N.: Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge University Press, New York (2000)
Schindelin, J., Arganda-Carreras, I., Frise, E., Kaynig, V., Longair, M., Pietzsch, T., Preibisch, S., Rueden, C., Saalfeld, S., Schmid, B., Tinevez, J.Y., White, D.J., Hartenstein, V., Eliceiri, K., Tomancak, P., Cardona, A.: Fiji: an open-source platform for biological-image analysis. Nat. Methods 9(7), 676–682 (2012)
Wagner, T., Lipinski, H.G.: IJBlob: An ImageJ library for connected component analysis and shape analysis. J. Open Res. Softw. 1(6), 68 (2013)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Sys. Man. Cyber. 9, 62–66 (1979)
Acknowledgments
This work was supported by the National Science Centre in Poland grant no. 2014/14/E/NZ6/00365 (G.C.) and partially by grant of Wroclaw Medical University No. PBmn-131 and PBmn-132, and UMED sponsorship account.
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Kulbacka, J., Kulbacki, M., Segen, J., Chodaczek, G., Dubinska-Magiera, M., Saczko, J. (2016). Cellular Nuclei Differentiation Evaluated by Automated Analysis of CLSM Images. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9622. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49390-8_40
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DOI: https://doi.org/10.1007/978-3-662-49390-8_40
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