Automatic Quantification of Immunohistochemically Stained Cell Nuclei Based on Standard Reference Cells
نویسندگان
چکیده
A fully automatic method for quantification of images of immunohistochemically stained cell nuclei by computing area proportions, is presented. Agarose embedded cultured fibroblasts were fixed, paraffin embedded and sectioned at 4 microm. They were then stained together with 4 microm sections of the test specimen obtained from bladder cancer material. A colour based classifier is automatically computed from the control cells. The method was tested on formalin fixed paraffin embedded tissue section material, stained with monoclonal antibodies against the Ki67 antigen and cyclin A protein. Ki67 staining results in a detailed nuclear texture with pronounced nucleoli and cyclin A staining is obtained in a more homogeneously distributed pattern. However, different staining patterns did not seem to influence labelling index quantification, and the sensitivity to variations in light conditions and choice of areas within the control population was low. Thus, the technique represents a robust and reproducible quantification method. In tests measuring proportions of stained area an average standard deviation of about 1.5% for the same field was achieved when classified with classifiers created from different control samples.
منابع مشابه
بررسی ایمونوهیستوشیمیایی نشانگرهای p1 و cyclin D1 در آملوبلاستومای فکین
Background and Aim: The cell cycle is an important event in tumor growth and differentiation and several molecules are involved in this process. The aim of this study was to evaluate the expression of cyclin D1 (a cell cycle inducer) and p21 (a cell cycle inhibitor) in ameloblastoma of the jaws. Materials and Methods: In this cross-sectional study, 40 cases of ameloblastoma were selected from t...
متن کاملAutomatic Quantification of Immunohistochemically Stained Cell Nuclei Using Unsupervised Image Analysis
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 P2/A-histogram, where P2/A is a global roundness measure. Then the image is transformed ...
متن کاملA multistep image analysis method to increase automated identification efficiency in immunohistochemical nuclear markers with a high background level
Background In anatomical and surgical pathology, the customary method of manual observation and measurement of immunohistochemically stained markers from microscopic images is tedious, expensive and time consuming. There is great demand for automated procedures for analyzing digital images (DIs) of these markers [1] given that they reduce human variability in the evaluation of stained markers [...
متن کاملCase Report: Effects of Image Compression on Automatic Count of Immunohistochemically Stained Nuclei in Digital Images
This study investigates the effects of digital image compression on automatic quantification of immunohistochemical nuclear markers. We examined 188 images with a previously validated computer-assisted analysis system. A first group was composed of 47 images captured in TIFF format, and other three contained the same images converted from TIFF to JPEG format with 3x, 23x and 46x compression. Co...
متن کاملA New Method for Segmentation of Colour Images Applied to Immunohistochemically Stained Cell Nuclei
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 cla...
متن کامل