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Semantic Segmentation of Cell Nuclei in Breast Cancer using Convolutional Neural Network

by Tomiya Said Ahmed Zarbega, Yasemin Gültepe
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 176 - Number 22
Year of Publication: 2020
Authors: Tomiya Said Ahmed Zarbega, Yasemin Gültepe
10.5120/ijca2020920133

Tomiya Said Ahmed Zarbega, Yasemin Gültepe . Semantic Segmentation of Cell Nuclei in Breast Cancer using Convolutional Neural Network. International Journal of Computer Applications. 176, 22 ( May 2020), 1-8. DOI=10.5120/ijca2020920133

@article{ 10.5120/ijca2020920133,
author = { Tomiya Said Ahmed Zarbega, Yasemin Gültepe },
title = { Semantic Segmentation of Cell Nuclei in Breast Cancer using Convolutional Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { May 2020 },
volume = { 176 },
number = { 22 },
month = { May },
year = { 2020 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume176/number22/31328-2020920133/ },
doi = { 10.5120/ijca2020920133 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:43:10.725059+05:30
%A Tomiya Said Ahmed Zarbega
%A Yasemin Gültepe
%T Semantic Segmentation of Cell Nuclei in Breast Cancer using Convolutional Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 176
%N 22
%P 1-8
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Many studies have been carried out in the literature and practice by using deep learning technique and successful results have been obtained. Convolutional Neural Network (CNN), a specialized architecture of deep learning, is particularly successful in image processing. Semantic segmentation is a computer vision task to estimate pixel tags corresponding to the region to which it belongs or to the region of the surrounding region. Semantic segmentation aims to understand the class of special objects in the scene. In this paper, Convolutional Neural Network based on detection and semantic segmentation of cell nuclei for breast cancer was performed on the “PSB 2015 crowdsourced nuclei” data set. As a result, the CNN model gave the highest performance with precision (0.844), recall (0.832) and accuracy (0.851) compared to other classifiers in the literature and the most advanced methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Convolution neural network image segmentation semantic segmentation nuclei cells breast cancer.

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