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- W2433864314 abstract "Noise removal from medical images is important for further processing and visual analysis. Medical images like X-Ray, CT, MRI, PET and SPECT have minute information about heart, brain and nerves. These images need to accurate and free from noise. Noise reduction plays an important role in medical imaging. There are various methods of noise removal such as filters, wavelets and thresholding based on wave lets. Although these methods produced good results but still have some limitations. Considering and analyzing the limitations of the previous methods our research presents Neuro-Fuzzy and SVM as proposed method. The proposed method removes the noise and improves the quality of the medical image. The quantitative analysis based on the standard metrics like peak signal-to-noise ratio and mean structural similarity index matrix shows that the proposed method performs better than the other recently proposed denoising methods for medical images." @default.
- W2433864314 created "2016-06-24" @default.
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- W2433864314 date "2014-01-01" @default.
- W2433864314 modified "2023-09-23" @default.
- W2433864314 title "AN EFFICIENT TECHNIQUE OF MEDICAL IMAGE NOISING AND DE-NOISING USING NEURO-FUZZY AND SVM (SUPPORT VECTOR MACHINE)-A REVIEW" @default.
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