Summary
The standardization method of immunohistchemically staining tissue section images prior to the image processing and analysis is described in this paper. The effectiveness of the proposed standardization method is examined on thin tissue slices of breast cancer stained with DAB & H. The image analysis results after the initial image standardization are more closer to the results of traditional methods of cells nuclei quantification than for original images.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Swerdlow, S., Campo, E., Harris, N., Jaffe, E., Pileri, S., et al.: WHO Classification of Tumours of Haematopoietic and Lymphoid Tissues. In: IARC (2007)
Seidal, T., Balaton, A.J., Battifora, H.: Interpretation and quantification of immunostains. The American Journal of Surgical Pathology 25(9), 1204–1207 (2001)
Yaziji, H., Barry, T.: Diagnostic immunohistochemistry: what can go wrong? Adv. Anat. Pathol. 13(5), 238–246 (2006)
Kayser, G., Radziszowski, D., Bzdyl, P., Sommer, R., Kayser, K.: Theory and implementation of an electronic, automated measurement system for images obtained from immunohistochemically stained slides. Anal. Quant. Cytol. Histol. 28(1), 27–38 (2006)
Kayser, K., Radziszowski, D., Bzdyl, P., Sommer, R., Kayser, G.: Towards an automated virtual slide screening: theoretical considerations and practical experiences of automated tissue-based virtual diagnosis to be implemented in the internet. Diagnostic Pathology 1(1), 10 (2006)
Hyun-Ju, C., Ik-Hwan, C., et al.: Color image analysis for quantifying renal tumor angiogenesis. Analyt. Quant. Cytl. Histol. 27, 43–51 (2005)
Bartels, P., Montironi, R., Duval da Silva, V., Hamilton, P., Thompson, D., et al.: Tissue architecture analysis inprostate cancer and its precursore: An innovative approach to computerized histometry. Rur. Urol. 35, 484–491 (1999)
Schulerud, H., Kristensen, G., Liestol, K., Vlatkovic, L., Reith, A., Albbregtsen, F., Danielsen, H.: A review of caveats in statistical nuclear image analysis. Analit. Cell. Pathol. 16, 63–82 (1998)
Kan, J., Qing-Min, L., Sheng-Yang, D.: A novel white blood cell segmentation scheme using scale-space filtering and watershed clustering. In: 2003 International Conference Machine Learning and Cybernetics, vol. 5, pp. 2820–2825 (2003)
Markiewicz, T., Wiśniewski, P., Osowski, S., Patera, J., Kozłowski, W., Koktysz, R.: Comparative analysis of methods for accurate recognition of cells through nuclei staining of KI-67 in neuroblastoma and estrogen/progesterone status staining in breast cancer. Analyt. Quant. Cytl. Histol. 31(1), 49–62 (2009)
Koprowski, R., Wróbel, Z.: Automatic segmentation of biological cell structures based on conditional opening or closing. MG&V 14, 285–307 (2005)
Markiewicz, T., Osowski, S., Pater, J., Kozłowski, W.: Image processing for accurate cell recognition and count on histologic slides. Analyt. Quant. Cytl. Histol. 28(5), 281–291 (2006)
Pavlopoulos, P., Zimeras, S., Kavantzas, N., Korkolopoulou, P., et al.: Segmentation of transitional cell carcinoma nuclei by nonsupervised thresholding in different color spaces. Anal. Quant. Cytol. Histol. 29(4), 271–278 (2007)
Wang, M., Zhou, X., Li, F., Huckins, J., King, R., Wong, S.: Novel cell segmentation and online svm for cell cycle phase identification in automated microscopy. Bioinformatics 24(1), 94–101 (2008)
Neuman, U., Korzyńska, A., Lopez, C., Lejeun, M.: Segmentation of stained lymphoma tissue section images. In: Pietka, E., Kawa, J. (eds.) Information Tech. and Biomedicine, ASC, Springer, Heidelberg (2010) (accepted)
Sung-Hyuk, C.: A fast hue-based colour image indexing algorithm. MG&V 11(2/3), 285–295 (2002)
Fu, K., Mui, J.: A survey on image segmentation. Pattern Recognition 13(1), 3–16 (1981)
Pham, D., Xu, C., Prince, J.: A survey of current methods in medical image segmentation. Annual Review of Biomedical Engineering 2, 315–338 (2000)
Iwanowski, M., Soille, P.: Morphological Refinement of an Image Segmentation. LNCS, pp. 538–545. Springer, Heidelberg (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Korzyńska, A., Neuman, U., Lopez, C., Lejeun, M., Bosch, R. (2010). The Method of Immunohistochemical Images Standardization. In: Choraś, R.S. (eds) Image Processing and Communications Challenges 2. Advances in Intelligent and Soft Computing, vol 84. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16295-4_24
Download citation
DOI: https://doi.org/10.1007/978-3-642-16295-4_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16294-7
Online ISBN: 978-3-642-16295-4
eBook Packages: EngineeringEngineering (R0)