Multimodal Medical Image Fusion Based on Parameter Adaptive PCNN and Latent Low-rank Representation

作     者：WANG Wenyan ZHOU Xianchun YANG Liangjian WANG Wenyan;ZHOU Xianchun;YANG Liangjian

作者机构：Nanjing University of Information Science and TechnologyNanjing 210044 

出 版 物：《Instrumentation》 (仪器仪表学报（英文版）)

年 卷 期：2023年第10卷第1期

页      面：45-58页

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 0836[工学-生物工程] 

主　　题：Image Fusion Non-subsampled Shearlet Transform Parameter Adaptive PCNN Latent Low-rank Representation 

摘      要：Medical image fusion has been developed as an efficient assistive technology in various clinical applications such as medical diagnosis and treatment *** at the problem of insufficient protection of image contour and detail information by traditional image fusion methods,a new multimodal medical image fusion method is *** method first uses non-subsampled shearlet transform to decompose the source image to obtain high and low frequency subband coefficients,then uses the latent low rank representation algorithm to fuse the low frequency subband coefficients,and applies the improved PAPCNN algorithm to fuse the high frequency subband ***,based on the automatic setting of parameters,the optimization method configuration of the time decay factorαe is carried *** experimental results show that the proposed method solves the problems of difficult parameter setting and insufficient detail protection ability in traditional PCNN algorithm fusion images,and at the same time,it has achieved great improvement in visual quality and objective evaluation indicators.