Anatomical and functional medical image fusion using sparse representation in NSST domain

作者：Tang Lu; Tian Chuangeng; Hu Junfeng; Zhang Shikun; Qian Jiansheng^*

来源：Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia, 2016, 39(7): 380-384.

DOI：10.21311/001.39.7.47

• Biomedical research
• Clinical diagnosis
• Fused images
• Image fusion techniques
• Learned dictionaries
• NSST domain
• Source images
• Sparse representation

The fusion of medical images is very useful for biomedical research and clinical diagnosis. An image fusion technique for Anatomical and functional medical image using sparse representation in NSST Domain is presented. Firstly, the source images are decomposed by NSST, which are sparsely represented with learned dictionaries. Then, max-ℓ0is selected as coefficients of the fused image. Finally, the fused image is reconstructed by performing inverse NSST. Visual and quantitative analysis of experimental results show that the proposed scheme is superior to state-of-art schemes.

• 出版日期2016
• 单位中国矿业大学（北京）