Shutao Li

Summary

Country: China

Publications

  1. doi Group-sparse representation with dictionary learning for medical image denoising and fusion
    Shutao Li
    College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
    IEEE Trans Biomed Eng 59:3450-9. 2012
  2. ncbi Fusing images with different focuses using support vector machines
    Shutao Li
    College of Electrical and Information Engineering, Hunan University, 410082 Changsha, PROC
    IEEE Trans Neural Netw 15:1555-61. 2004
  3. doi An efficient dictionary learning algorithm and its application to 3-D medical image denoising
    Shutao Li
    College of Electrical and Information Engineering, Hunan University, Changsha 410082, China shutao_li yahoo com cn
    IEEE Trans Biomed Eng 59:417-27. 2012

Detail Information

Publications3

  1. doi Group-sparse representation with dictionary learning for medical image denoising and fusion
    Shutao Li
    College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
    IEEE Trans Biomed Eng 59:3450-9. 2012
    ..The experimental results on 3-D image denoising and image fusion demonstrate the superiority of our proposed denoising and fusion approaches...
  2. ncbi Fusing images with different focuses using support vector machines
    Shutao Li
    College of Electrical and Information Engineering, Hunan University, 410082 Changsha, PROC
    IEEE Trans Neural Netw 15:1555-61. 2004
    ..Experimental results show that the proposed method outperforms the traditional approach both visually and quantitatively...
  3. doi An efficient dictionary learning algorithm and its application to 3-D medical image denoising
    Shutao Li
    College of Electrical and Information Engineering, Hunan University, Changsha 410082, China shutao_li yahoo com cn
    IEEE Trans Biomed Eng 59:417-27. 2012
    ..The experiments on both synthetically generated data and real 3-D medical images demonstrate that the proposed approach has superior performance compared to some well-known methods...