research-article

Hidden Markov Random Field model and BFGS algorithm for Brain Image Segmentation

Authors:

EL-Hachemi Guerrout,

Samy Ait-Aoudia,

Dominique Michelucci,

Ramdane MahiouAuthors Info & Claims

MedPRAI-2016: Proceedings of the Mediterranean Conference on Pattern Recognition and Artificial Intelligence

Pages 7 - 11

https://doi.org/10.1145/3038884.3038886

Published: 22 November 2016 Publication History

Abstract

Brain MR images segmentation has attracted a particular focus in medical imaging. The automatic image analysis and interpretation became a necessity. Segmentation is one of the key operations to provide a crucial decision support to physicians. Its goal is to simplify the representation of an image into items meaningful and easier to analyze. Hidden Markov Random Fields (HMRF) provide an elegant way to model the segmentation problem. This model leads to the minimization problem of a function. BFGS (Broyden-Fletcher-Goldfarb-Shanno algorithm) is one of the most powerful methods to solve unconstrained optimization problem. This paper presents how we combine HMRF and BFGS to achieve a good segmentation. Brain image segmentation results are evaluated on ground-truth images, using the Dice coefficient.

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Cited By

Guerrout EAit-Aoudia SMichelucci DMahiou R(2018)Conjugate Gradient Method for Brain Magnetic Resonance Images SegmentationComputational Intelligence and Its Applications10.1007/978-3-319-89743-1_48(561-572)Online publication date: 12-Apr-2018
https://doi.org/10.1007/978-3-319-89743-1_48

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Published In

cover image ACM Other conferences

MedPRAI-2016: Proceedings of the Mediterranean Conference on Pattern Recognition and Artificial Intelligence

November 2016

163 pages

ISBN:9781450348768

DOI:10.1145/3038884

General Chairs:
Chawki Djeddi
Larbi Tebessi University, Algeria
,
Imran Siddiqi
Bahria University, Pakistan
,
Akram Bennour
Larbi Tebessi University, Algeria
,
Program Chairs:
Youcef Chibani
University of Science and Technology Houari Boumediene, Algeria
,
Haikal El Abed
Technical Trainers College, German International Cooperation, Kingdom of Saudi Arabia

Copyright © 2016 ACM.

© 2016 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 November 2016

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MedPRAI-2016

MedPRAI-2016: Mediterranean Conference on Pattern Recognition and Artificial Intelligence

November 22 - 23, 2016

Tebessa, Algeria

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Cited By

Guerrout EAit-Aoudia SMichelucci DMahiou R(2018)Conjugate Gradient Method for Brain Magnetic Resonance Images SegmentationComputational Intelligence and Its Applications10.1007/978-3-319-89743-1_48(561-572)Online publication date: 12-Apr-2018
https://doi.org/10.1007/978-3-319-89743-1_48

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