ArticleMedical image analysis2019
Surface-constrained volumetric registration for the early developing brain.
Article in Medical image analysis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- Unified Brain Surface and Volume Registration.... International Conference on Learning Representations · 2026Article
- VINNA for neonates: Orientation independence through latent augmentations.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Diffusion MRI harmonization via personalized template mapping.Human brain mapping · 2024Article
- Characterization of dynamic patterns of human fetal to neonatal brain asymmetry with deformation-based morphometry.Frontiers in neuroscience · 2023Article
- MRI of the Neonatal Brain: A Review of Methodological Challenges and Neuroscientific Advances.Journal of magnetic resonance imaging : JMRI · 2021Review
- Surface-Volume Consistent Construction of Longitudinal Atlases for the Early Developing Brain.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2019Article
- Surface-Guided Image Fusion for Preserving Cortical Details in Human Brain Templates.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted InterventionArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The T1-weighted and T2-weighted MRI contrasts of the infant brain evolve drastically during the first year of life. This poses significant challenges to inter- and intra-subject registration, which is key to subsequent statistical analyses. Existing registration methods that do not consider temporal contrast changes are ineffective for infant brain MRI data. To address this problem, we present in this paper a method for deformable registration of infant brain MRI. The key advantage of our method is threefold: (i) To deal with appearance changes, registration is performed based on segmented tissue maps instead of image intensity. Segmentation is performed by using an infant-centric algorithm previously developed by our group. (ii) Registration is carried out with respect to both cortical surfaces and volumetric tissue maps, thus allowing precise alignment of both cortical and subcortical structures. (iii) A dynamic elasticity model is utilized to allow large non-linear deformation. Experimental results in comparison with well-established registration methods indicate that our method yields superior accuracy in both cortical and subcortical alignment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.