An Improved Image Segmentation System: A Cooperative Multi-agent Strategy for 2D/3D Medical Images
Abstract
In this paper, we present a solution-based cooperation approach for strengthening the image segmentation. This paper proposes a cooperative method relying on Multi-Agent System. The main contribution of this work is to highlight the importance of cooperation between the contour and region growing based on Multi-Agent System (MAS). Consequently, agents’ interactions form the main part of the whole process for image segmentation. Similar works were proposed to evaluate the effectiveness of the proposed solution. The main difference is that our Multi-Agent System can perform the segmentation process ensuring efficiency. Our results show that the performance indices in the system were higher. Furthermore, the integration of the cooperation paradigm allows to speed up the segmentation process. Besides, the tests reveal the robustness of our method by proving competitive results. Our proposal achieved an accuracy of 93,51%± 0,8, a sensitivity of 93,53%± 5,08 and a specificity rate of 92,64%± 4,01.
Keywords
Artificial intelligence, Intelligent systems, Computer applications, Expert systems, Image processing
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
H. Allioui, M. Sadgal and A. El Fazziki, "An Improved Image Segmentation System: A Cooperative Multi-agent Strategy for 2D/3D Medical Images," in Journal of Communications Software and Systems, vol. 16, no. 2, pp. 143-155, April 2020, doi: 10.24138/jcomss.v16i2.830
@article{allioui2020improvedimage,
author = {Hanane Allioui and Mohamed Sadgal and Aziz El Fazziki},
title = {An Improved Image Segmentation System: A Cooperative Multi-agent Strategy for 2D/3D Medical Images},
journal = {Journal of Communications Software and Systems},
month = {4},
year = {2020},
volume = {16},
number = {2},
pages = {143--155},
doi = {10.24138/jcomss.v16i2.830},
url = {https://doi.org/10.24138/jcomss.v16i2.830}
}