loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: El-Hachemi Guerrout 1 ; Samy Ait-Aoudia 1 ; Dominique Michelucci 2 and Ramdane Mahiou 1

Affiliations: 1 Ecole Nationale Supérieure en Informatique, Algeria ; 2 Université de Bourgogne, France

ISBN: 978-989-758-173-1

Keyword(s): Medical Image Segmentation, Hidden Markov Random Field, Nelder-Mead, Torczon, Kappa Index.

Related Ontology Subjects/Areas/Topics: Classification ; Clustering ; Pattern Recognition ; Theory and Methods

Abstract: The goal of image segmentation is to simplify the representation of an image to items meaningful and easier to analyze. Medical image segmentation is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There is no one way to perform the segmentation. There are several methods based on HMRF. Hidden Markov Random Fields (HMRF) constitute an elegant way to model the problem of segmentation. This modelling leads to the minimization of an energy function. In this paper we investigate direct search methods that are Nelder-Mead and Torczon methods to solve this optimization problem. The quality of segmentation is evaluated on grounds truths images using the Kappa index called also Dice Coefficient (DC). The results show the supremacy of the methods used compared to others methods.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.236.216.93

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Guerrout, E.; Ait-Aoudia, S.; Michelucci, D. and Mahiou, R. (2016). Hidden Markov Random Fields and Direct Search Methods for Medical Image Segmentation.In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 154-161. DOI: 10.5220/0005658501540161

@conference{icpram16,
author={El{-}Hachemi Guerrout. and Samy Ait{-}Aoudia. and Dominique Michelucci. and Ramdane Mahiou.},
title={Hidden Markov Random Fields and Direct Search Methods for Medical Image Segmentation},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={154-161},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005658501540161},
isbn={978-989-758-173-1},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Hidden Markov Random Fields and Direct Search Methods for Medical Image Segmentation
SN - 978-989-758-173-1
AU - Guerrout, E.
AU - Ait-Aoudia, S.
AU - Michelucci, D.
AU - Mahiou, R.
PY - 2016
SP - 154
EP - 161
DO - 10.5220/0005658501540161

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.