Medical Image Segmentation Using Kernal Based Fuzzy C-Means Algorithm
| Research Area: | Volume 4 Issue 1, Jan. 2015 | Year: | 2015 |
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| Type of Publication: | Article | Keywords: | FCM, Mean Filtering, Median Filtering, Image Segmentation, Gaussian Kernal, Fuzzy, Multiple-Kernal |
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| Journal: | IJEIR | Volume: | 4 |
| Number: | 1 | Pages: | 207-212 |
| Month: | Jan.-Feb. | ||
| ISSN: | 2277-5668 | ||
| Abstract: | In this paper, a new segmentation algorithm with the integration of mean and peak-and-valley filtering based denoising and Gaussian kernels based fuzzy c-means (MPVKFCM) algorithm is proposed for medical image segmentation. First, the image is denoised by using the mean and peak-and-valley filtering algorithm. Secondly, image segmentation algorithm with Gaussian kernels based fuzzy c-means is performed on the denoised image. The performance of the proposed algorithm is tested on OASIS-MRI image dataset. The performance is tested in terms of score, number of iterations (NI), Execution time (TM) and PSNR values under different Gaussian noises on OASIS-MRI dataset. The results after investigation, the proposed method shows a significant improvement as compared to other existing methods in terms of PSNR, Score, NI and TM under different Gaussian noises on OASIS-MRI dataset. |
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Full text:
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IJEIR-1396_final.pdf
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