3D-Guided Backward Iterative Structural Refinement for Histology-to-MRI Registration

Qitai Sun, Xiao Li, Han Zhang, Chenjie Jia, Xiaowei He, Tuo Zhang, Yudan Ren

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

Abstract

Histology-to-MRI volume registration is an important preprocessing procedure in brain structure quantification, brain structure mapping, and pathological research of brain diseases. However, there are still many challenges preventing precise registration, especially the complex deformation of slices during sectioning, distinct modality of images and sparse slices intervals. To improve registration accuracy, a 3D-guided backward iterative structural refinement registration method is proposed in this paper. Inspired by the thought of the back-propagation algorithm, this method indirectly obtains the structural information during each registration iteration, continuously finetunes the registration results, and successively achieves improvement in registration accuracy. According to several validation and contrast experiments, this method is demonstrated to be robust and effective. This method can be widely applied in solving histology-to-MRI registration problem.

Original languageEnglish
Title of host publicationIEEE International Symposium on Biomedical Imaging, ISBI 2024 - Conference Proceedings
PublisherIEEE Computer Society
ISBN (Electronic)9798350313338
DOIs
StatePublished - 2024
Event21st IEEE International Symposium on Biomedical Imaging, ISBI 2024 - Athens, Greece
Duration: 27 May 202430 May 2024

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452

Conference

Conference21st IEEE International Symposium on Biomedical Imaging, ISBI 2024
Country/TerritoryGreece
CityAthens
Period27/05/2430/05/24

Keywords

  • histological slices
  • histology-to-MRI registration
  • Image registration
  • MRI structure volume

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