MATEC Web Conf.
Volume 125, 201721st International Conference on Circuits, Systems, Communications and Computers (CSCC 2017)
|Number of page(s)||4|
|Published online||04 October 2017|
Milk duct segmentation in microscopic HE images of breast cancer tissues
1 Faculty of Applied Informatics & Mathematics, Warsaw University of Life Sciences, Warsaw, Poland
2 Faculty of Electrical Engineering, Warsaw University of Technology, Warsaw, Poland
3 Faculty of Electronics, Military University of Technology, Warsaw, Poland
The aim of the paper is to recognize and extract the milk duct in haematoxylin and eosin (HE) stained breast cancer tissues. The paper presents the modified K-means approach to segmentation of the milk duct in HE stained images. Instead of using single pixels we propose to consider the defined region of pixels in the process. Thanks to such modification more accurate extraction of the milk ducts has been achieved. To compare the results in a numerical way the GT images prepared by the medical expert have been subtracted from the corresponding images created by the segmentation methods. The numerical experiments performed for many preparations have confirmed the superiority of such approach. The proposed method has allowed reducing significantly the error of duct segmentation in comparison to the classical K-means approaches. The results show, that our method is superior to the standard K-means and to the K-means preceded by averaging or Gaussian filtration at different size of filtration mask.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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