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Fuzzy clustering role in breast image

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Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. Ravindraiah and K. Ravindraiah , K. Tejaswini Published Computer Science. Medical image segmentation plays a vital role in one of the most challenging fields of engineering.
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SAR image change detection method based on intuitionistic fuzzy C-means clustering algorithm

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Metrics details. The proposed CAD system firstly compensates motion artifacts and segments the breast region. Then, the potential lesion voxels are detected and used as the initial seed points for the seeded region-growing algorithm. A new and robust region-growing algorithm incorporating with Fuzzy C-means FCM clustering and vesselness filter is proposed to segment any potential lesion regions. Subsequently, the false positive detections are reduced by applying a discrimination step.
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A Survey of Image Segmentation Algorithms Based On Fuzzy Clustering

The goal of this study was to develop an automated method to segment breast masses on dynamic contrast-enhanced DCE magnetic resonance MR scans and to evaluate its potential for estimating tumor volume on pre- and postchemotherapy images and tumor change in response to treatment. The corresponding VOIs over the entire time sequence were then automatically extracted. A new 3D VOI representing the local pharmacokinetic activities in the VOI was generated from the 4D VOI sequence by summarizing the temporal intensity enhancement curve of each voxel with its standard deviation. The method then used the fuzzy c -means FCM clustering algorithm followed by morphological filtering for initial mass segmentation. The initial segmentation was refined by the 3D level set LS method.
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Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Fuzzy c-means algorithm for medical image segmentation Abstract: Clustering of data is a method by which large sets of data are grouped into clusters of smaller sets of similar data. Fuzzy c-means FCM clustering algorithm is one of the most commonly used unsupervised clustering technique in the field of medical imaging.

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