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Reseach Article

Medical Image Segmentation using Modified Morphological Reconstruction

by A. Nithya, R. Kayalvizhi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 2
Year of Publication: 2014
Authors: A. Nithya, R. Kayalvizhi
10.5120/14958-3129

A. Nithya, R. Kayalvizhi . Medical Image Segmentation using Modified Morphological Reconstruction. International Journal of Computer Applications. 86, 2 ( January 2014), 20-26. DOI=10.5120/14958-3129

@article{ 10.5120/14958-3129,
author = { A. Nithya, R. Kayalvizhi },
title = { Medical Image Segmentation using Modified Morphological Reconstruction },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 2 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 20-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number2/14958-3129/ },
doi = { 10.5120/14958-3129 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:03:11.059968+05:30
%A A. Nithya
%A R. Kayalvizhi
%T Medical Image Segmentation using Modified Morphological Reconstruction
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 2
%P 20-26
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The objective of this research is to improve the accuracy of object segmentation in medical images by constructing an object segmentation algorithm. Image segmentation is a crucial step in the field of image processing and pattern recognition. Segmentation allows the identification of structures in an image which can be utilized for further processing. Both region-based and object-based segmentation are utilized in a robust and principled manner. Gradient based MultiScalE Graylevel mOrphological recoNstructions (G-SEGON) is used for segmenting an image. SEGON roughly identifies the background and object regions in the image. The proposed method takes advantage of segmentation of both gray scale image and color image.

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Index Terms

Computer Science
Information Sciences

Keywords

G-SEGON Grey level mesh opening and closing reconstruction gradient K-mean clustering accuracy