CT and MRI image fusion based on weight difference between L1 and L2 norm

Xuan Yang, Qingchao Zeng, Xun Liu, Qingliang Jiao, Ming Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

MRI and CT image fusion, which combines the features of MRI and CT images to obtain high quality images, is a significant domain. In this paper, a novel image fusion algorithm based on the weight difference between L1 and L2 norm and tight wavelet frame is presented. We first proposed the fusion model of MRI and CT images, and then proposed to apply alternate multiplier method to solve the model. Experiments show that both CT and T1-weighted MRI, CT and T2-weighted MRI, or CT and PD-weighted MRI, our proposed algorithm can achieve balance in the source images and obtain the fusion image with the best effect, which will be beneficial to help doctors make accurate diagnosis.

Original languageEnglish
Title of host publication2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages285-288
Number of pages4
ISBN (Electronic)9780738131221
DOIs
Publication statusPublished - 26 Mar 2021
Event2nd IEEE International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021 - Nanchang, China
Duration: 26 Mar 202128 Mar 2021

Publication series

Name2021 IEEE 2nd International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021

Conference

Conference2nd IEEE International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering, ICBAIE 2021
Country/TerritoryChina
CityNanchang
Period26/03/2128/03/21

Keywords

  • CT
  • L1 and L2 norm
  • MRI
  • fusion
  • tight wavelet frame

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