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Reseach Article

Brain Tumor Segmentation using SLIC Superpixels and Optimized Thresholding Algorithm

by Prince Ebenezer Adjei, Henry Nunoo-Mensah, Richard Junior Amedzrovi Agbesi, Joyce Raissa Yaho Ndjanzoue
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 20
Year of Publication: 2018
Authors: Prince Ebenezer Adjei, Henry Nunoo-Mensah, Richard Junior Amedzrovi Agbesi, Joyce Raissa Yaho Ndjanzoue
10.5120/ijca2018917915

Prince Ebenezer Adjei, Henry Nunoo-Mensah, Richard Junior Amedzrovi Agbesi, Joyce Raissa Yaho Ndjanzoue . Brain Tumor Segmentation using SLIC Superpixels and Optimized Thresholding Algorithm. International Journal of Computer Applications. 181, 20 ( Oct 2018), 1-5. DOI=10.5120/ijca2018917915

@article{ 10.5120/ijca2018917915,
author = { Prince Ebenezer Adjei, Henry Nunoo-Mensah, Richard Junior Amedzrovi Agbesi, Joyce Raissa Yaho Ndjanzoue },
title = { Brain Tumor Segmentation using SLIC Superpixels and Optimized Thresholding Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2018 },
volume = { 181 },
number = { 20 },
month = { Oct },
year = { 2018 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number20/29998-2018917915/ },
doi = { 10.5120/ijca2018917915 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:06:27.224993+05:30
%A Prince Ebenezer Adjei
%A Henry Nunoo-Mensah
%A Richard Junior Amedzrovi Agbesi
%A Joyce Raissa Yaho Ndjanzoue
%T Brain Tumor Segmentation using SLIC Superpixels and Optimized Thresholding Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 20
%P 1-5
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper deals with the implementation of a simple algorithm for automatic brain tumor segmentation. Brain tumor is commonly diagnosed by Computer tomography and Magnetic Resonance Imaging in clinical treatment. The paper uses Simple Linear Iterative Clustering (SLIC) to segment brain images according to their spatial and color proximities. The ratio of the mean and variance of the image pixels are determined in order to obtain an optimum threshold value. Region merging after thresholding was carried out. The final output image was an image with tumor sections circled out. The segmentation adheres to boundaries and the procedure is fast and reproducible.

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Index Terms

Computer Science
Information Sciences

Keywords

SLIC brain tumour region merging image thresholding