@inproceedings{SisLab1200,
       booktitle = {The 7th International Conference on Advanced Technologies for Communications (ATC 2014)},
           month = {October},
           title = {An Effective Example-based Denoising Method for CT Images using Markov Random Field},
          author = {Dinh Hoan Trinh and Thanh Trung Nguyen and Linh Trung Nguyen},
            year = {2014},
           pages = {355--359},
        keywords = {Gaussian noise;Markov processes;computerised tomography;image denoising;medical image processing;CT images;Gaussian denoising;Markov random field;example-based denoising method;high-frequency band;patch pairs;Biomedical imaging;Computed tomography;Databases;Image denoising;Noise;Noise measurement;Noise reduction},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/1200/},
        abstract = {We propose in this paper a novel example-based method for Gaussian denoising of CT images. In the proposed method, denoising is performed with the help of a set of example CT images. We construct, from the example images, a database consisting of high and low-frequency patch pairs and then use the Markov random field to denoise. The proposed denoising method can restore the high-frequency band that is often lost by the traditional noise-filters. Moreover, it is very effective for images corrupted by heavy noise. Experimental results also show that the proposed method outperforms other state-of-the-art denoising methods both in the objective and subjective evaluations.}
}