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In this paper, the automatic segmentation of Osteosar-coma in MRI images is formed as a clustering problem. Subsequently, a new dynamic clustering algorithm based on the Harmony Search (HS) hybridized with Fuzzy C-means (FCM) called DCHS is proposed to automatically segment the Osteosarcoma MRI images in an intelligent manner. The concept of variable length in each harmony memory vector is applied...
Automatic brain MRI image segmentation is a challenging problem and received significant attention in the field of medical image processing. In this paper, we present a new dynamic clustering algorithm based on the Harmony Search (HS) hybridized with Fuzzy C-means called DCHS to automatically segment the brain MRI image in an intelligent manner. In this algorithm, the capability of standard HS is...
Image segmentation is considered as one of the crucial steps in image analysis process and it is the most challenging task. Image segmentation can be modeled as a clustering problem. Therefore, clustering algorithms have been applied successfully in image segmentation problems. Fuzzy c-mean (FCM) algorithm is considered as one of the most popular clustering algorithm. Even that, FCM can generate a...
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