Medical images denoising based on total variation algorithm

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Because of the limitation of equipment and the transmission process, the medical images' quality is dropped, which cannot satisfy the medical analysis and the applied requirements. The denoising of medical image plays an important role in the image processing, and it is the basic of further analysis and computation. The image edge are easily interrupted by noise, but the traditional image denoising smooth out the edges of the reconstructed images which caused edge to be blurred, and made the information lost. The denoising algorithms based on partial differential of total variation is proposed by analyzing the requirements of medical image features from the view of image denoising, and use the OpenCV platform to simulate the program. The emphasis is to study the algorithm which applies in the medical image denoising technique. Theoretical analysis and experimental results show that the algorithm is effectiveness and superiority, which can make sure to obtain clear medical image and preserve the edge information integrally at the same time. © 2011 Published by Elsevier Ltd.




Li, B., & Que, D. S. (2011). Medical images denoising based on total variation algorithm. In Procedia Environmental Sciences (Vol. 8, pp. 227–234). Elsevier B.V.

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