ABSTRACT
Objective: To fuse many non-homologous medical images based on wavelet transformation, and integrate and stand out complementation information, and strengthen image quality, and reduce redundancy so as to enhance the precision of clinically auxiliary diagnosis and treatment for medical image. Methods: Through studied and researched the relevant knowledge of wavelet theory in the application of image fusion to proposed a improved fusion algorithm by mutual combination for maximum low frequency energy and maximum high frequency variance. The fusion experiment of non-homologous standard medical image, including CT, MRI and multi-focus images, were implemented, and their data were compared. And then, the performance of image fusion was compared and analyzed under different fusion rule and different fusion method. Results: In the two kinds of contrastive analysis experiments, the fusion image which depended on algorithm included more abundantly effective information amount of source image, and the luminance of image was reasonable enhanced. Besides, the mean value, mutual information and information entropy of fusion image were optimal. Conclusion: The fusion image which comes from multimoding medical image algorithm has better visual effects and quantization indicator, and it has strengthener fused performance. Therefore, it can reflect the effectiveness of the method.
ABSTRACT
Objective To propose an improved discrete wavelet transform (DWT ) and to apply it in multimodal medical im‐age fusion .Methods Firstly ,the source medical images were initially transformed into the high frequency and low frequency images by DWT ;then the high frequency part adopted the big direction absolute values ,which effectively preserved the detailed informa‐tion of image ,while the low frequency part used the fusion rule of local energy ratio for preserving the most of image information ;finally ,the discrete wavelet reverse transform was used for reconstructing the fusion sub‐images into fusion image .Results By comparing the fusion images by 3 groups of medical images ,this proposed algorithm was superior to other existing algorithms in the aspects of subjective visual effect and objective evaluation indicators .Conclusion The proposed algorithm of medical image fusion is rapid and accurate ,has excellent performance in the noise environment and clinical examples ,can obtain the high quality fusion im‐age and has higher clinical application value .