Analytical Cellular Pathology

Analytical Cellular Pathology / 2004 / Article

Open Access

Volume 26 |Article ID 241921 | https://doi.org/10.1155/2004/241921

Armin Gerger, Patrick Bergthaler, Josef Smolle, "An Automated Method for the Quantification and Fractal Analysis of Immunostaining", Analytical Cellular Pathology, vol. 26, Article ID 241921, 10 pages, 2004. https://doi.org/10.1155/2004/241921

An Automated Method for the Quantification and Fractal Analysis of Immunostaining

Received17 Oct 2003
Accepted22 Mar 2004

Abstract

Aims. In tissue counter analysis (TCA) digital images of complex histologic sections are dissected into elements of equal size and shape, and digital information comprising grey level, colour and texture features is calculated for each element. In this study we assessed the feasibility of TCA for the quantitative description of amount and also of distribution of immunostained material. Methods. In a first step, our system was trained for differentiating between background and tissue on the one hand and between immunopositive and so‐called other tissue on the other. In a second step, immunostained slides were automatically screened and the procedure was tested for the quantitative description of amount of cytokeratin (CK) and leukocyte common antigen (LCA) immunopositive structures. Additionally, fractal analysis was applied to all cases describing the architectural distribution of immunostained material. Results. The procedure yielded reproducible assessments of the relative amounts of immunopositive tissue components when the number and percentage of CK and LCA stained structures was assessed. Furthermore, a reliable classification of immunopositive patterns was found by means of fractal dimensionality. Conclusions. Tissue counter analysis combined with classification trees and fractal analysis is a fully automated and reproducible approach for the quantitative description in immunohistology.

Copyright © 2004 Hindawi Publishing Corporation and the authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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