Publication | Closed Access
Mammogram image segmentation using fuzzy clustering
15
Citations
16
References
2012
Year
Unknown Venue
Fuzzy LogicMachine VisionImage AnalysisMedical ImagingEngineeringPattern RecognitionMammogram ImageFuzzy C-meansBreast ImagingComputer-aided DiagnosisFuzzy Pattern RecognitionMedical Image ComputingMammogram Image SegmentationFuzzy ClusteringImage SegmentationMedian FilterRadiologyHealth Sciences
This paper proposes mammogram image segmentation using Fuzzy C-Means (FCM) clustering algorithm. The median filter is used for pre-processing of image. It is normally used to reduce noise in an image. The 14 Haralick features are extracted from mammogram image using Gray Level Co-occurrence Matrix (GLCM) for different angles. The features are clustered by K-Means and FCM algorithms inorder to segment the region of interests for further classification. The performance of segmentation result of the proposed algorithm is measured according to the error values such as Mean Square Error (MSE) and Root Means Square Error (RMSE). The Mammogram images used in our experiment are obtained from MIAS database.
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