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Performance and Evalution of Guassian Kernals for FCM Algorithm With Mean Filtering Based Denoising For MRI Segmentation | |
Venu, Nookala | |
通讯作者 | Venu, Nookala |
会议名称 | 3rd International Conference on Communications and Signal Processing (ICCSP) |
会议日期 | APR 03-05, 2014 |
会议地点 | Melmaruvathur, INDIA |
英文摘要 | 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 de noised 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 and (TM) 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 Score, NI and TM under different Gaussian noises on OASIS-MRI dataset. |
英文关键词 | FCM Mean Filtering median filtering Image Segmentation Gaussian Kernal fuzzy multiple-kernal |
来源出版物 | 2014 INTERNATIONAL CONFERENCE ON COMMUNICATIONS AND SIGNAL PROCESSING (ICCSP) |
出版年 | 2014 |
EISBN | 978-1-4799-3358-7 |
出版者 | IEEE |
类型 | Proceedings Paper |
语种 | 英语 |
国家 | India |
收录类别 | CPCI-S |
WOS记录号 | WOS:000357940500348 |
WOS关键词 | C-MEANS ALGORITHM ; IMAGE SEGMENTATION ; FUZZY |
WOS类目 | Engineering, Electrical & Electronic ; Telecommunications |
WOS研究方向 | Engineering ; Telecommunications |
资源类型 | 会议论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/302854 |
作者单位 | (1)Sri Venkateswara Univ, Coll Engn, Dept Elect & Commun Engn, Tirupati 517502, Andhra Pradesh, India |
推荐引用方式 GB/T 7714 | Venu, Nookala. Performance and Evalution of Guassian Kernals for FCM Algorithm With Mean Filtering Based Denoising For MRI Segmentation[C]:IEEE,2014. |
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