ArticleIEEE transactions on medical imaging2022
Deep Diffusion MRI Registration (DDMReg): A Deep Learning Method for Diffusion MRI Registration.
Article in IEEE transactions on medical imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- A systematic review of automated methods to perform white matter tract segmentation.Frontiers in neuroscience · 2024Pooled it
- U-Swing: An Adaptive U-Net and Swin Fusion for WB-MRI Whole Spine Bone Marrow Segmentation.Journal of imaging informatics in medicine · 2026Article
- HERON: High-Efficiency Real-Time Motion Quantification and Re-Acquisition for Fetal Diffusion MRI.IEEE transactions on medical imaging · 2025Article
- FetDTIAlign: A deep learning framework for affine and deformable registration of fetal brain dMRI.NeuroImage · 2025Article
- Generative AI Models in Time-Varying Biomedical Data: Scoping Review.Journal of medical Internet research · 2025Article
- Field-of-view extension for brain diffusion MRI via deep generative models.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- MMORF-FSL's MultiMOdal Registration Framework.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- DDParcel: Deep Learning Anatomical Brain Parcellation From Diffusion MRI.IEEE transactions on medical imaging · 2024Article
- Diffusion MRI with Machine Learning.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Geometric Deep Learning for Unsupervised Registration of Diffusion Magnetic Resonance Images.Information processing in medical imaging : proceedings of the ... conference · 2023Article
- Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation across populations and dMRI acquisitions.Medical image analysis · 2023Article
- Convergence of Artificial Intelligence and Neuroscience towards the Diagnosis of Neurological Disorders-A Scoping Review.Sensors (Basel, Switzerland) · 2023Article
- Digital Analysis of Smart Registration Methods for Magnetic Resonance Images in Public Healthcare.Frontiers in public health · 2022Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
In this paper, we present a deep learning method, DDMReg, for accurate registration between diffusion MRI (dMRI) datasets. In dMRI registration, the goal is to spatially align brain anatomical structures while ensuring that local fiber orientations remain consistent with the underlying white matter fiber tract anatomy. DDMReg is a novel method that uses joint whole-brain and tract-specific information for dMRI registration. Based on the successful VoxelMorph framework for image registration, we propose a novel registration architecture that leverages not only whole brain information but also tract-specific fiber orientation information. DDMReg is an unsupervised method for deformable registration between pairs of dMRI datasets: it does not require nonlinearly pre-registered training data or the corresponding deformation fields as ground truth. We perform comparisons with four state-of-the-art registration methods on multiple independently acquired datasets from different populations (including teenagers, young and elderly adults) and different imaging protocols and scanners. We evaluate the registration performance by assessing the ability to align anatomically corresponding brain structures and ensure fiber spatial agreement between different subjects after registration. Experimental results show that DDMReg obtains significantly improved registration performance compared to the state-of-the-art methods. Importantly, we demonstrate successful generalization of DDMReg to dMRI data from different populations with varying ages and acquired using different acquisition protocols and different scanners.
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