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Selective Brain MRI Image Segmentation using Fuzzy C Mean Clustering Algorithm for Tumor Detection
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 144 - Number 7 |
| Year of Publication: 2016 |
| Authors: Jesmon G. Paul, Tarun Kumar Rawat, Josna Job |
10.5120/ijca2016910455
|
Jesmon G. Paul, Tarun Kumar Rawat, Josna Job . Selective Brain MRI Image Segmentation using Fuzzy C Mean Clustering Algorithm for Tumor Detection. International Journal of Computer Applications. 144, 7 ( Jun 2016), 28-31. DOI=10.5120/ijca2016910455
Abstract
Brain MRI (Magnetic Resonance Imaging)[1] images are used to diagnose any abnormality associated with human brain by the physicians. But these images are often corrupted with noise which makes it difficult to diagnose any abnormality in initial stage of defect. Image processing techniques like image segmentation is used to extract important information out of noisy MRI images. But image segmentation process will also remove original minute details available in original image apart from noise because entire image will be clustered into few segments of same pixel intensity. In this paper a selective brain MRI image segmentation is proposed based on Fuzzy C Mean (FCM) Clustering algorithm [2] with image pixel weightage to retain necessary original image details intact.
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