Medical Image Segmentation by Active Contour Improvement

Abdelaziz Essadike; Elhoussaine Ouabida; Abdenbi Bouzid

doi:doi:10.11648/j.ajsea.20170602.11

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Medical Image Segmentation by Active Contour Improvement

Abdelaziz Essadike, Elhoussaine Ouabida, Abdenbi Bouzid

Published in American Journal of Software Engineering and Applications (Volume 6, Issue 2)

Received: 13 March 2017 Accepted: 22 March 2017 Published: 3 April 2017

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Abstract

This paper introduces a new medical image segmentation approach based on active contour improvement. The boundaries in brain images are detected using an original technique of active contour improved by a Region of Interest (ROI) extraction. We compare the results of the proposed model to Chane-Vese active contour model and Caselles’s et al. Geodesic active contour model. Experimental results of brain boundary localization on a national center of Oncology’s database demonstrate the promising performance of this method.

Published in	American Journal of Software Engineering and Applications (Volume 6, Issue 2)
DOI	10.11648/j.ajsea.20170602.11
Page(s)	13-17
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Medical Image Segmentation, Active Contours, Energy Minimization, ROI, Level Sets

References

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APA Style

Abdelaziz Essadike, Elhoussaine Ouabida, Abdenbi Bouzid. (2017). Medical Image Segmentation by Active Contour Improvement. American Journal of Software Engineering and Applications, 6(2), 13-17. https://doi.org/10.11648/j.ajsea.20170602.11

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ACS Style

Abdelaziz Essadike; Elhoussaine Ouabida; Abdenbi Bouzid. Medical Image Segmentation by Active Contour Improvement. Am. J. Softw. Eng. Appl. 2017, 6(2), 13-17. doi: 10.11648/j.ajsea.20170602.11

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AMA Style

Abdelaziz Essadike, Elhoussaine Ouabida, Abdenbi Bouzid. Medical Image Segmentation by Active Contour Improvement. Am J Softw Eng Appl. 2017;6(2):13-17. doi: 10.11648/j.ajsea.20170602.11

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@article{10.11648/j.ajsea.20170602.11,
  author = {Abdelaziz Essadike and Elhoussaine Ouabida and Abdenbi Bouzid},
  title = {Medical Image Segmentation by Active Contour Improvement},
  journal = {American Journal of Software Engineering and Applications},
  volume = {6},
  number = {2},
  pages = {13-17},
  doi = {10.11648/j.ajsea.20170602.11},
  url = {https://doi.org/10.11648/j.ajsea.20170602.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20170602.11},
  abstract = {This paper introduces a new medical image segmentation approach based on active contour improvement. The boundaries in brain images are detected using an original technique of active contour improved by a Region of Interest (ROI) extraction. We compare the results of the proposed model to Chane-Vese active contour model and Caselles’s et al. Geodesic active contour model. Experimental results of brain boundary localization on a national center of Oncology’s database demonstrate the promising performance of this method.},
 year = {2017}
}

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TY  - JOUR
T1  - Medical Image Segmentation by Active Contour Improvement
AU  - Abdelaziz Essadike
AU  - Elhoussaine Ouabida
AU  - Abdenbi Bouzid
Y1  - 2017/04/03
PY  - 2017
N1  - https://doi.org/10.11648/j.ajsea.20170602.11
DO  - 10.11648/j.ajsea.20170602.11
T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
JO  - American Journal of Software Engineering and Applications
SP  - 13
EP  - 17
PB  - Science Publishing Group
SN  - 2327-249X
UR  - https://doi.org/10.11648/j.ajsea.20170602.11
AB  - This paper introduces a new medical image segmentation approach based on active contour improvement. The boundaries in brain images are detected using an original technique of active contour improved by a Region of Interest (ROI) extraction. We compare the results of the proposed model to Chane-Vese active contour model and Caselles’s et al. Geodesic active contour model. Experimental results of brain boundary localization on a national center of Oncology’s database demonstrate the promising performance of this method.
VL  - 6
IS  - 2
ER  -

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Author Information

Abdelaziz Essadike

Optronic and Information Treatment Team, Atomic, Mechanical, Photonic and Energy Laboratory, Faculty of Science, Moulay Ismail University, Zitoune, Meknès, Morocco
Elhoussaine Ouabida

Optronic and Information Treatment Team, Atomic, Mechanical, Photonic and Energy Laboratory, Faculty of Science, Moulay Ismail University, Zitoune, Meknès, Morocco
Abdenbi Bouzid

Optronic and Information Treatment Team, Atomic, Mechanical, Photonic and Energy Laboratory, Faculty of Science, Moulay Ismail University, Zitoune, Meknès, Morocco

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APA Style

Abdelaziz Essadike, Elhoussaine Ouabida, Abdenbi Bouzid. (2017). Medical Image Segmentation by Active Contour Improvement. American Journal of Software Engineering and Applications, 6(2), 13-17. https://doi.org/10.11648/j.ajsea.20170602.11

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ACS Style

Abdelaziz Essadike; Elhoussaine Ouabida; Abdenbi Bouzid. Medical Image Segmentation by Active Contour Improvement. Am. J. Softw. Eng. Appl. 2017, 6(2), 13-17. doi: 10.11648/j.ajsea.20170602.11

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AMA Style

Abdelaziz Essadike, Elhoussaine Ouabida, Abdenbi Bouzid. Medical Image Segmentation by Active Contour Improvement. Am J Softw Eng Appl. 2017;6(2):13-17. doi: 10.11648/j.ajsea.20170602.11

Copy | Download

@article{10.11648/j.ajsea.20170602.11,
  author = {Abdelaziz Essadike and Elhoussaine Ouabida and Abdenbi Bouzid},
  title = {Medical Image Segmentation by Active Contour Improvement},
  journal = {American Journal of Software Engineering and Applications},
  volume = {6},
  number = {2},
  pages = {13-17},
  doi = {10.11648/j.ajsea.20170602.11},
  url = {https://doi.org/10.11648/j.ajsea.20170602.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20170602.11},
  abstract = {This paper introduces a new medical image segmentation approach based on active contour improvement. The boundaries in brain images are detected using an original technique of active contour improved by a Region of Interest (ROI) extraction. We compare the results of the proposed model to Chane-Vese active contour model and Caselles’s et al. Geodesic active contour model. Experimental results of brain boundary localization on a national center of Oncology’s database demonstrate the promising performance of this method.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Medical Image Segmentation by Active Contour Improvement
AU  - Abdelaziz Essadike
AU  - Elhoussaine Ouabida
AU  - Abdenbi Bouzid
Y1  - 2017/04/03
PY  - 2017
N1  - https://doi.org/10.11648/j.ajsea.20170602.11
DO  - 10.11648/j.ajsea.20170602.11
T2  - American Journal of Software Engineering and Applications
JF  - American Journal of Software Engineering and Applications
JO  - American Journal of Software Engineering and Applications
SP  - 13
EP  - 17
PB  - Science Publishing Group
SN  - 2327-249X
UR  - https://doi.org/10.11648/j.ajsea.20170602.11
AB  - This paper introduces a new medical image segmentation approach based on active contour improvement. The boundaries in brain images are detected using an original technique of active contour improved by a Region of Interest (ROI) extraction. We compare the results of the proposed model to Chane-Vese active contour model and Caselles’s et al. Geodesic active contour model. Experimental results of brain boundary localization on a national center of Oncology’s database demonstrate the promising performance of this method.
VL  - 6
IS  - 2
ER  -

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