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Reseach Article

A Method for Automatic Tumor Segmentation from Image of Brain

by Samir Kumar Bandyopadhyay
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 17 - Number 6
Year of Publication: 2011
Authors: Samir Kumar Bandyopadhyay
10.5120/2224-2834

Samir Kumar Bandyopadhyay . A Method for Automatic Tumor Segmentation from Image of Brain. International Journal of Computer Applications. 17, 6 ( March 2011), 24-27. DOI=10.5120/2224-2834

@article{ 10.5120/2224-2834,
author = { Samir Kumar Bandyopadhyay },
title = { A Method for Automatic Tumor Segmentation from Image of Brain },
journal = { International Journal of Computer Applications },
issue_date = { March 2011 },
volume = { 17 },
number = { 6 },
month = { March },
year = { 2011 },
issn = { 0975-8887 },
pages = { 24-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume17/number6/2224-2834/ },
doi = { 10.5120/2224-2834 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:04:53.911174+05:30
%A Samir Kumar Bandyopadhyay
%T A Method for Automatic Tumor Segmentation from Image of Brain
%J International Journal of Computer Applications
%@ 0975-8887
%V 17
%N 6
%P 24-27
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

It is difficult to differentiate to between tumor and tissue in the brain when the border and cells overlapped between normal and abnormal tissues in gray level of the medical images. This is a real challenge of the surgeon or physician to distinguish it. When MRI and CT scan are taken for patient brain tumor there is an overlapping between the boundaries of tumor in the cerebellum part and tissue surrounded. If the surgeon has the accurate dimensions of the involved tissue he can do his job with more flexibility. When the image of MRI and CT scan were taken to a patient it is easy to distinguish image gray level overlapping between two or more different parts in the same image.

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Index Terms

Computer Science
Information Sciences

Keywords

MRI image CT image Gray level Tumor Segmentation