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Volume 8, Issue 3
Automatic Segmentation Approach Based Data Aggregation for the Classification of Brain Tissues

Lamiche Chaabane and Moussaoui Abdelouahab

J. Info. Comput. Sci. , 8 (2013), pp. 209-216.

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  • Abstract
The paper presents a study and an evaluation of a novel unsupervised segmentation technique based aggregation approach and some of possibility theory concepts. Firstly, the MPFCM (Modified Possibilistic Fuzzy C-Means) algorithm is used to extract information from each of MR images modalities. In second step, an obtained data are combined with an operator in order to exploiting the uncertainty and ambiguity in the images. Finally, the segmented image is constructed using a decision rule. The efficiency of the proposed method is demonstrated by segmentation experiments using simulated MR images with different noise levels.
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@Article{JICS-8-209, author = {Lamiche Chaabane and Moussaoui Abdelouahab}, title = {Automatic Segmentation Approach Based Data Aggregation for the Classification of Brain Tissues}, journal = {Journal of Information and Computing Science}, year = {2024}, volume = {8}, number = {3}, pages = {209--216}, abstract = { The paper presents a study and an evaluation of a novel unsupervised segmentation technique based aggregation approach and some of possibility theory concepts. Firstly, the MPFCM (Modified Possibilistic Fuzzy C-Means) algorithm is used to extract information from each of MR images modalities. In second step, an obtained data are combined with an operator in order to exploiting the uncertainty and ambiguity in the images. Finally, the segmented image is constructed using a decision rule. The efficiency of the proposed method is demonstrated by segmentation experiments using simulated MR images with different noise levels. }, issn = {1746-7659}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jics/22612.html} }
TY - JOUR T1 - Automatic Segmentation Approach Based Data Aggregation for the Classification of Brain Tissues AU - Lamiche Chaabane and Moussaoui Abdelouahab JO - Journal of Information and Computing Science VL - 3 SP - 209 EP - 216 PY - 2024 DA - 2024/01 SN - 8 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22612.html KW - aggregation, possibility theory, segmentation, MPFCM, MR images. AB - The paper presents a study and an evaluation of a novel unsupervised segmentation technique based aggregation approach and some of possibility theory concepts. Firstly, the MPFCM (Modified Possibilistic Fuzzy C-Means) algorithm is used to extract information from each of MR images modalities. In second step, an obtained data are combined with an operator in order to exploiting the uncertainty and ambiguity in the images. Finally, the segmented image is constructed using a decision rule. The efficiency of the proposed method is demonstrated by segmentation experiments using simulated MR images with different noise levels.
Lamiche Chaabane and Moussaoui Abdelouahab. (2024). Automatic Segmentation Approach Based Data Aggregation for the Classification of Brain Tissues. Journal of Information and Computing Science. 8 (3). 209-216. doi:
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