Open AccessQuantification of epithelial volume by image processing applied to ovarian tumors
Author(s) -
Schipper N. W.,
Smeulders A. W. M.,
Baak J. P. A.
Publication year - 1987
Publication title -
cytometry
Language(s) - English
Resource type - Journals
eISSN - 1097-0320
pISSN - 0196-4763
DOI - 10.1002/cyto.990080402
Subject(s) - serous fluid , image processing , stromal cell , ovarian tissue , feulgen stain , epithelium , stroma , pathology , segmentation , biology , image (mathematics) , ovary , artificial intelligence , computer science , medicine , immunohistochemistry , staining , endocrinology
This paper describes an image analysis technique for automated estimation of the percentages of epithelium and stroma in (tumor) tissue. The program is evaluated on ovarian tumors of the serous, mucinous, and endometrioid type. From standard paraffin sections, stained with pararosanilin Feulgen and naphthol yellow, a blue‐yellow image pair was recorded. The blue image was used for the determination of the total tissue area and the yellow image for the epithelial area. For the latter the image processing method is based on the fact that epithelial nuclei are generally more tightly packed than stromal nuclei. A structural approach was applied, in which the segmentation of the nuclei was based on the image contrast range in thedensity domain. The method has been tested with 78 image pairs from 19 ovarian tumors with varying degrees of malignancy. The area percentages, as assessed with image processing, were strongly correlated to control percentages, established by interactive morphometry (r = 0.98).