RC-Block: Refinement Coefficient for Rectifying Deformation Field

  • Suwei Zhang
  • , Tai Ma
  • , Ying Wen*
  • *Corresponding author for this work

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

1 Scopus citations

Abstract

In deformable image registration, learning-based methods have demonstrated impressive performance. However, previous methods mainly focus on enhancing the capability to predict the deformation field, without fully exploring the optimal ways to update the deformation field. As a result, errors can easily accumulate during the process of updating the deformation field, thus leading to inaccurate registration results. To solve this problem, we propose RC-Block (Refinement Coefficient Block) to find the optimal way to update the deformation field, thus achieving high accuracy registration results. The proposed module introduces a novel refinement coefficient, which can leverage information from the current scale to continuously rectify the previous deformation field. In addition, RC-Block is a plug-and-play module that can be seamlessly and easily integrated into most registration methods. Extensive experimental results show that our module can effectively improve existing advanced methods' performance with minimal additional burden.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Multimedia and Expo, ICME 2024
PublisherIEEE Computer Society
ISBN (Electronic)9798350390155
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Multimedia and Expo, ICME 2024 - Niagra Falls, Canada
Duration: 15 Jul 202419 Jul 2024

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

Conference2024 IEEE International Conference on Multimedia and Expo, ICME 2024
Country/TerritoryCanada
CityNiagra Falls
Period15/07/2419/07/24

Keywords

  • Convolutional Neural Network
  • Deformable Image Registration
  • Deformation Field
  • Plug-and-Play Module
  • Refinement Coefficient

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