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Article type: Research Article
Authors: Ranefall, Petter; | Egevad, Lars | Nordin, Bo | 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: petter@cb.uu.se.
Abstract: A new method for segmenting images of immunohistochemically stained cell nuclei is presented. The aim is to distinguish between cell nuclei with a positive staining reaction and other cell nuclei, and to make it possible to quantify the reaction. First, a new supervised algorithm for creating a pixel classifier is applied to an image that is typical for the sample. The training phase of the classifier is very user friendly since only a few typical pixels for each class need to be selected. The classifier is robust in that it is non‐parametric and has a built‐in metric that adapts to the colour space. After the training the classifier can be applied to all images from the same staining session. Then, all pixels classified as belonging to nuclei of cells are grouped into individual nuclei through a watershed segmentation and connected component labelling algorithm. This algorithm also separates touching nuclei. Finally, the nuclei are classified according to their fraction of positive pixels.
Keywords: Colour image segmentation, immunohistochemical staining, pixelwise classification, relaxation, watershed segmentation, automated cell counting
Journal: Analytical Cellular Pathology, vol. 15, no. 3, pp. 145-156, 1997
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