Medical Image Denoising Using Neighboring Coefficients Preservation

被引:0
|
作者
Yang, Ying [1 ]
Wei, Yusen [1 ]
Yang, Ming [2 ]
机构
[1] Xian Univ Technol, Dept Elect Engn, Xian, Peoples R China
[2] ZTE R&D Ctr, Project Management Dept 1, Xian, Peoples R China
基金
中国国家自然科学基金;
关键词
Wavelet transform; Neighboring coefficients; Medical images;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The artifacts arising from the imaging devices decrease the accuracy of medical diagnosis. In order to decrease the effect of artifacts, the neighboring coefficients preservation scheme is extended to remove the noise in the medical images. If the magnitude of a coefficient is larger than the threshold, all its neighboring coefficients will be preserved in the thresholding denoising in our studies. Every coefficient is properly processed by considering its neighboring characteristics so that the performance of image denoising can be effectively improved. Several denoising methods were used to compare with our method. The numerical results and visual perceptions illustrated that our method was superior to the conventional thresholding denoising methods and could be effectively used for different medical images denoising.
引用
收藏
页码:149 / 154
页数:6
相关论文
共 50 条
  • [11] Image Denoising Algorithm Using Adaptive Neighboring Window and Threshold Value
    Hussain, Sabahaldin A.
    Gorashi, Sami M. A.
    2015 INTERNATIONAL CONFERENCE ON COMPUTING, CONTROL, NETWORKING, ELECTRONICS AND EMBEDDED SYSTEMS ENGINEERING (ICCNEEE), 2015, : 168 - 172
  • [12] Image Denoising Using Three Scales of Wavelet Coefficients
    Chen, Guangyi
    Zhu, Wei-Ping
    ADVANCES IN NEURAL NETWORKS - ISNN 2008, PT 2, PROCEEDINGS, 2008, 5264 : 376 - 383
  • [13] Image denoising using derotated complex wavelet coefficients
    Miller, Mark
    Kingsbury, Nick
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2008, 17 (09) : 1500 - 1511
  • [14] IMAGE DENOISING USING CONTEXTUAL MODELING OF CURVELET COEFFICIENTS
    Kechichian, R.
    Amiot, C.
    Girard, C.
    Pescatore, J.
    Chanussot, J.
    Desvignes, M.
    2014 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2014, : 2659 - 2663
  • [15] Medical Image Denoising using Sparse Representations
    Abousaleh, Fatma S.
    Yu, Neng-Hao
    Hua, Kai-Lung
    Cheng, Wen-Huang
    2017 IEEE 8TH INTERNATIONAL CONFERENCE ON AWARENESS SCIENCE AND TECHNOLOGY (ICAST), 2017, : 422 - 427
  • [16] Improved wavelet denoising using neighboring coefficients and its application to machinery fault diagnosis
    Yang, S. (yangsp@stdu.edu.cn), 1600, Chinese Mechanical Engineering Society (49):
  • [17] Medical image denoising using wavelet thresholding
    Fourati, W
    Kammoun, F
    Bouhlel, MS
    2005 Beijing International Conference on Imaging: Technology and Applications for the 21st Century, 2005, : 260 - 261
  • [18] Medical image denoising using wavelet thresholding
    Fourati, W
    Kammoun, F
    Bouhlel, MS
    JOURNAL OF TESTING AND EVALUATION, 2005, 33 (05) : 364 - 369
  • [19] Image denoising using curvelet transform: an approach for edge preservation
    Patil, Anil A.
    Singhai, Jyoti
    JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH, 2010, 69 (01): : 34 - 38
  • [20] An Improved Adaptive Wavelet Denoising Method Based on Neighboring Coefficients
    Jiang, Jun
    Guo, Jian
    Fan, Weihua
    Chen, Qingwei
    2010 8TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION (WCICA), 2010, : 2894 - 2898