An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentation
Clustering algorithms are widely used to segment medical images. However, these techniques are difficult to perform, especially in brain magnetic resonance images (MRI), given the complexity of the anatomical structure of brain tissue, the in-homogeneity of pixel intensity in these images, and part...
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| Format: | Article |
| Language: | English |
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Asociación Española para la Inteligencia Artificial
2023-06-01
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| Series: | Inteligencia Artificial |
| Subjects: | |
| Online Access: | http://journal.iberamia.org/index.php/intartif/article/view/948 |
| _version_ | 1827895963054768128 |
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| author | ghazi boumediene ghaouti Boudjelal Meftah |
| author_facet | ghazi boumediene ghaouti Boudjelal Meftah |
| author_sort | ghazi boumediene ghaouti |
| collection | DOAJ |
| description |
Clustering algorithms are widely used to segment medical images. However, these techniques are difficult to perform, especially in brain magnetic resonance images (MRI), given the complexity of the anatomical structure of brain tissue, the in-homogeneity of pixel intensity in these images, and partial volume and noise effects. This will cause the algorithm to fall into the local minima problem; for this reason, it is recommended to improve such clustering algorithms using optimization techniques to obtain better results. In this study, we have proposed a developed clustering algorithm and we optimized it using a tree seed algorithm (TSA) to segment brain MRI image. Algorithms are tested on real brain image datasets. The experimental results on simulated and real brain MRI datasets show that our proposed method has satisfactory results regarding the Davies-Bouldin index (DBI) compared to the fuzzy c-mean (FCM) algorithm.
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| first_indexed | 2024-03-12T22:28:06Z |
| format | Article |
| id | doaj.art-e1930ddac38d4392936a23ba5d9d80b1 |
| institution | Directory Open Access Journal |
| issn | 1137-3601 1988-3064 |
| language | English |
| last_indexed | 2024-03-12T22:28:06Z |
| publishDate | 2023-06-01 |
| publisher | Asociación Española para la Inteligencia Artificial |
| record_format | Article |
| series | Inteligencia Artificial |
| spelling | doaj.art-e1930ddac38d4392936a23ba5d9d80b12023-07-21T20:41:10ZengAsociación Española para la Inteligencia ArtificialInteligencia Artificial1137-36011988-30642023-06-012672An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentationghazi boumediene ghaouti0Boudjelal Meftah1Mustapha Stambouli University, Mascara, AlgeriaMustapha Stambouli University, Mascara, Algeria Clustering algorithms are widely used to segment medical images. However, these techniques are difficult to perform, especially in brain magnetic resonance images (MRI), given the complexity of the anatomical structure of brain tissue, the in-homogeneity of pixel intensity in these images, and partial volume and noise effects. This will cause the algorithm to fall into the local minima problem; for this reason, it is recommended to improve such clustering algorithms using optimization techniques to obtain better results. In this study, we have proposed a developed clustering algorithm and we optimized it using a tree seed algorithm (TSA) to segment brain MRI image. Algorithms are tested on real brain image datasets. The experimental results on simulated and real brain MRI datasets show that our proposed method has satisfactory results regarding the Davies-Bouldin index (DBI) compared to the fuzzy c-mean (FCM) algorithm. http://journal.iberamia.org/index.php/intartif/article/view/948Edge detectionSegmentationBrain MRI imageTree seed algorithm |
| spellingShingle | ghazi boumediene ghaouti Boudjelal Meftah An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentation Inteligencia Artificial Edge detection Segmentation Brain MRI image Tree seed algorithm |
| title | An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentation |
| title_full | An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentation |
| title_fullStr | An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentation |
| title_full_unstemmed | An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentation |
| title_short | An Optimized Clustering Approach using Tree Seed Algorithm for the Brain MRI Images Segmentation |
| title_sort | optimized clustering approach using tree seed algorithm for the brain mri images segmentation |
| topic | Edge detection Segmentation Brain MRI image Tree seed algorithm |
| url | http://journal.iberamia.org/index.php/intartif/article/view/948 |
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