Reducing impurities in medical images based on curvelet domain

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Abstract

Medical image quality greatly affects the diagnostic process. Most of the tasks of increasing the quality of medical images are deblurring or denoising process. These tasks are the difficult problems in medical image processing because they must keep edge features. In the cases, the medical images that have blur combined with noise are a more difficult problem. In this paper, we proposed a method for reducing impurities in medical images based on curvelet domain. The proposed method uses curvelet coefficient combined with augmented lagrangian function to denoising combined with deblurring in medical images. For evaluating the results of the proposed method, we have compared the results with the other recent methods available in literature.

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Tuyet, V. T. H., & Binh, N. T. (2015). Reducing impurities in medical images based on curvelet domain. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST (Vol. 144, pp. 306–319). Springer Verlag. https://doi.org/10.1007/978-3-319-15392-6_29

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