Fully automatic multisegmentation approach for magnetic resonance imaging brain tumor detection using improved region‐growing and quasi‐Monte Carlo‐expectation maximization algorithm-Reference-Cited by-同舟云学术

Fully automatic multisegmentation approach for magnetic resonance imaging brain tumor detection using improved region‐growing and quasi‐Monte Carlo‐expectation maximization algorithm

Published:2019-11-06 Issue:1 Volume:30 Page:104-111
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int J Imaging Syst Technol

Author:

Hachemi Belkacem¹²^ORCID,Chama Zouaoui²³,Alim‐Ferhat Fatiha¹,Lamini El‐Sedik⁴⁵,Abderrahmane Abdelkader⁶,Anani Macho²,Choquet Catherine³

Affiliation:

1. Division architecture et système multimédiaCentre de Développement des Technologies Avancées Alger Algeria

2. Department of ElectronicsDjillali Liabes University Sidi‐Bel‐Abbes Algeria

3. Laboratoire MIAUniversité de la Rochelle La Rochelle France

4. Faculty of Mathematics, RECITS LaboratoryUniversity of Science and Technology Houari Boumediene Algiers Algeria

5. Division Microélectronique et NanotechnologieCentre de Développement des Technologies Avancées Alger Algeria

6. Department of Physics, Faculty of Exact Sciences and InformaticsAbdelhamid Ibn Badis University Mostaganem Algeria

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ima.22376

Reference20 articles.

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5. MaitiI ChakrabortyM. A new method for brain tumor segmentation based on watershed and edge detection algorithms in HSV colour model. Paper presented at: 2012 National Conference on Computing and Communication Systems; 2012:1–5.

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