Abstract
Medical imaging is playing an effective role in diagnosing diseases noninvasively. There are many denoising filters, but previous filters have not attained the desirable results. Denoising techniques have to be applied in such a way that, they preserve and enhance diagnostic relevant information of the MRI images. Therefore noise reduction has always been a challenge for researchers. A hybrid denoising technique based on Sylvester-Lyapunov Equation and Non Local Means method has been proposed in this work. This hybrid denoising technique has been compared with the existing techniques of denoising by varying noise levels in brain images of Brainweb dataset and real dataset. Efficiency of methods have been discussed by measuring PSNR and SSIM coefficients.
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Acknowledgements
We want to thank UGC for funding this work under the category of Minor Research Project. We would like to thank University of Kota, Kota for supporting and providing resources to complete this work. We also thank to dr. dheeraj sharma, medical officer, Govt. of Rajasthan, India for helping in this work.
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Kumar Sharma, K., Gurjar, D., Jyotyana, M., Kumari, V. (2019). Denoising of Brain MRI Images Using a Hybrid Filter Method of Sylvester-Lyapunov Equation and Non Local Means. In: Tiwari, S., Trivedi, M., Mishra, K., Misra, A., Kumar, K. (eds) Smart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 851. Springer, Singapore. https://doi.org/10.1007/978-981-13-2414-7_46
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DOI: https://doi.org/10.1007/978-981-13-2414-7_46
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