Beta
ManageSearchChatDiscover
125382

Quantitative Comparison of Four Brain MRI Segmentation Techniques.

Article

Last updated: 22 Jan 2023

OverviewSimilar Items

Subjects

-

Tags

Computer Engineering and Systems

Abstract

Magnetic resonance jmaging (MRI) is an advanced medical imaging technique providing rich information about the human soft tissue anatomy. The goal of brain magnetic resonance image segmentation is to accurately identify the principal tissue structures in these image volumes. There are many methods that exist to segment the brain. One of these, conventional methods that use pure image processing techniques are not preferred because they need human interaction for accurate and reliable segmentation. Unsupervised methods, on the other hand, do not require any human interference and can segment the brain with high precision, in the light to this fact, we in this paper compare the performance of our image segmentation techniques in the subject of brain MR image. Results show that fuzzy Kohonen's Competitive Learning Algorithms performs better in terms of segmentation accuracy, while FCM performs better in terms of speed of computation 

DOI

10.21608/bfemu.2020.125382

Authors

First Name

A.

Last Name

Riad

MiddleName

M.

Affiliation

Head of information System Department

Email

amriad2000@yahoo.com

City

-

Orcid

-

First Name

Hamdy

Last Name

Elminir

MiddleName

K.

Affiliation

Kafr El-Sheikh University., Faculty of Engineering, Department of Electrical Engineering., Kafr El-Sheikh., Egypt.

Email

hamdy_elminir@hotmail.com

City

201203107427

Orcid

-

First Name

R.

Last Name

Mostaffa

MiddleName

R.

Affiliation

Faculty of Computer and Information Sciences. Mansoura University, Mansoura, Egypt

Email

-

City

-

Orcid

-

Volume

34

Article Issue

1

Related Issue

18587

Issue Date

2009-03-01

Receive Date

2009-01-09

Publish Date

2020-11-25

Page Start

1

Page End

13

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 34_Issue 1_Pages 1-13.pdf

PDF . 569.9kB

Link

https://bfemu.journals.ekb.eg/article_125382.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=125382

Order

6

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023