Automatic quantification of immunohistochemically stained cell nuclei using unsupervised image analysis

Article type: Research Article

Authors: Ranefall, Petter^; | Wester, Kenneth | Bengtsson, Ewert

Affiliations: Centre for Image Analysis, Uppsala University, Sweden | Department of Pathology, Uppsala University, Sweden

Note: [] Correspondence to: Petter Ranefall, Centre for Image Analysis, Lägerhyddvägen 17, S‐752 37 Uppsala, Sweden. Tel.: +46 18 471 78 49; Fax: +46 18 55 34 47; E‐mail: [email protected].

Abstract: A method for quantification of images of immunohistochemically stained cell nuclei by computing area proportions is presented. The image is transformed by a principal component transform. The resulting first component image is used to segment the objects from the background using dynamic thresholding of the P^2/A‐histogram, where P^2/A is a global roundness measure. Then the image is transformed into principal component hue, defined as the angle around the first principal component. This image is used to segment positive and negative objects. The method is fully automatic and the principal component approach makes it robust with respect to illumination and focus settings. An independent test set consisting of images grabbed with different focus and illumination for each field of view was used to test the method, and the proposed method showed less variation than the intraoperator variation using supervised Maximum Likelihood classification.

Keywords: Image analysis, principal components, automatic quantification, immunohistochemically stained cell nuclei

Journal: Analytical Cellular Pathology, vol. 16, no. 1, pp. 29-43, 1998