Medical Image Fusion Algorithm Based on NSST and Deep Learning
With the improvement of computer performance and the development of digital image processing technology,the medical image processing technology has been more widely used,such as the automatic analysis of medical images,the simulation of medical images,etc. Therefore,a medical image fusion method based on combining NSST and VGGNet19 deep learning network is proposed. First,the NSST decomposition of the medical source images was performed to obtain the low-frequency information and the high-frequency information of MRI and CT,respectively. Secondly,the low frequency information selects the fusion rule of guided filter and weighted equalization. The high frequency information extracts the image features with VGGNet19 network,and the final high frequency information is obtained through the rules of L1 regularization,upsampling and weighted equalization. The experimental results show that this method has a better fusion effect,which is good reflected in both subjective evaluation and objective indicators.
NETL
NSTL
万方数据
