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A multiscale algorithm for computing realistic image transformations – Application to the modelling of fetal brain growth

  • Centre de Recherche des Cordeliers

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

Abstract

We propose to establish a continuous trajectory of brain growth across pregnancy using geodesic regression in the Large Deformation Diffeomorphic Metric Mapping framework. One is usually faced with two issues when estimating high dimensional transformations: the elevated risk of trapping the optimization in an unrealistic local minimum and the fact that deformations are constrained to a single scale. To tackle these issues, we introduce a coarse-to-fine optimization strategy based on multiscale parametrizations of objects and deformations. Experiments on fetal brain Magnetic Resonance Images show that the multiscale strategy can generate more natural images of the fetal brain across pregnancy, which offers an interesting perspective for the quantitative analysis of normal and abnormal brain growth.

Original languageEnglish
Title of host publicationMedical Imaging 2023
Subtitle of host publicationImage Processing
EditorsOlivier Colliot, Ivana Isgum
PublisherSPIE
ISBN (Electronic)9781510660335
DOIs
Publication statusPublished - 1 Jan 2023
EventMedical Imaging 2023: Image Processing - San Diego, United States
Duration: 19 Feb 202323 Feb 2023

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume12464
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2023: Image Processing
Country/TerritoryUnited States
CitySan Diego
Period19/02/2323/02/23

Keywords

  • Atlas Estimation
  • Computational Anatomy
  • Fetal Brain Atlas
  • Fetal Brain Magnetic Resonance Imaging
  • Geodesic Regression
  • Multiscale Optimization

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