多模态医学图像融合方法的研究进展  

Research progress of multimodal medical image fusion methods

作　　者：陈伟[1,2,3,4] 孙康康 李奇轩[2,3,4] 谢凯 倪昕晔 CHEN Wei;SUN Kangkang;LI Qixuan;XIE Kai;NI Xinye(School of Computer Science and Artificial Intelligence,Changzhou University,Changzhou 213164 China;Department of Radiotherapy the Second People's Hospital of Changzhou Affiliated to Nanjing Medical University,Changzhou 213003 China;Central Laboratory of Medical Physics,Nanjing Medical University,Changzhou 213003 China;Jiangsu Province Engineering Research Center of Medical Physics,Changzhou 213003 China)

机构地区：[1]常州大学计算机与人工智能学院,江苏常州213164 [2]南京医科大学附属常州第二人民医院放疗科,江苏常州213003 [3]南京医科大学医学物理研究中心,江苏常州213003 [4]江苏省医学物理工程研究中心,江苏常州213003

出　　处：《中国辐射卫生》2023年第5期580-585,共6页Chinese Journal of Radiological Health

基　　金：江苏省重点研发计划社会发展项目(BE2022720);江苏省卫健委面上项目(M2020006);江苏省医学重点学科建设单位项目(JSDW202237)。

摘　　要：在目前的临床诊断中,医学图像已经成为重要的诊断依据,不同模态的医学图像会给出不同组织信息和功能信息。单模态图像只能给出单一诊断信息,无法诊断疑难杂症,需要多种诊断信息加持才能得出全面且准确的诊断结果。多模态融合技术可将多模态的医学图像融合到单模态的图像中,且单模态图像具有多种模态图像间的互补信息,从而在单一图像中得到充足的便于临床诊断的信息。本文将多模态医学图像融合方法整理为两种,分别为传统融合方法和基于深度学习的融合方法。In the current clinical diagnosis,medical images have become an important basis for diagnosis,and different modes of medical images provide different tissue information and functional information.Single-mode images can only provide single diagnostic information,by which difficult and complicated diseases cannot be diagnosed,and comprehensive and accurate diagnostic results can be obtained only with the help of multiple diagnostic information.The multimodal fusion technology fuses multiple modes of medical images into single-mode images,and thus the single-mode images contain complementary information between multiple modes of images,so that sufficient information for clinical diagnosis can be obtained in a single image.In this paper,the multimodal medical image fusion methods are sorted into two types,namely the traditional fusion method and the fusion method based on deep learning.

关 键 词：多模态 图像融合 深度学习 临床诊断 

分 类 号：R445[医药卫生—影像医学与核医学]