ArticleBrain imaging and behavior2018
Multi-site harmonization of diffusion MRI data in a registration framework.
Article in Brain imaging and behavior, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed.
- The role of white matter microstructure in the association between childhood maltreatment and adult post-traumatic symptoms.Molecular psychiatry · 2026Article
- Diffusion MRI sampling schemes bias diffusion metrics and tractography.Frontiers in neuroimaging · 2026Article
- Dose-dependent white matter changes associated with repetitive head impacts in former American football players.Brain communications · 2026Article
- Harmonizing 10,000 connectomes: site-invariant representation learning for multi-site analysis of network connectivity and cognitive impairment.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Utility of Harmonisation for Fixel-Based Metrics in Travelling Subjects and Alzheimer's Disease Data.Human brain mapping · 2025Article
- Effect of a consistent reconstruction algorithm on inter-scanner reproducibility in diffusion MRI.Medical physics · 2025Article
- Deep Learning for fODF Estimation in Infant Brains: Model Comparison, Ground-Truth Impact, and Domain Shift Mitigation.Human brain mapping · 2025Article
- Estimating Brain Similarity Networks With Diffusion MRI.Human brain mapping · 2025Article
- Toward diffusion MRI in the diagnosis and treatment of pancreatic cancer.Medical oncology (Northwood, London, England) · 2025Review
- Learning disentangled representations to harmonize connectome network measures.Journal of medical imaging (Bellingham, Wash.) · 2025Article
- Combining Biology-based and MRI Data-driven Modeling to Predict Response to Neoadjuvant Chemotherapy in Patients with Triple-Negative Breast Cancer.Radiology. Artificial intelligence · 2025Article
- Article
- MidRISH: Unbiased harmonization of rotationally invariant harmonics of the diffusion signal.Magnetic resonance imaging · 2024Article
- Voxel-Wise Fusion of 3T and 7T Diffusion MRI Data to Extract more Accurate Fiber Orientations.Brain topography · 2024Article
- Perfusion imaging by arterial spin labeling in migraine: A literature review.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2024Review
- A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations.Scientific data · 2024Article
- Topological abnormalities of the morphometric similarity network of the cerebral cortex in schizophrenia.Schizophrenia (Heidelberg, Germany) · 2024Article
- Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.Schizophrenia bulletin · 2024Article
- Diffusion MRI harmonization via personalized template mapping.Human brain mapping · 2024Article
- Harmonized diffusion MRI data and white matter measures from the Adolescent Brain Cognitive Development Study.Scientific data · 2024Article
3 more citing papers are in PubMed but not listed here.
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Authors and funding
23 authors.
Funding
Abstract
Diffusion MRI (dMRI) data acquired on different scanners varies significantly in its content throughout the brain even if the acquisition parameters are nearly identical. Thus, proper harmonization of such data sets is necessary to increase the sample size and thereby the statistical power of neuroimaging studies. In this paper, we present a novel approach to harmonize dMRI data (the raw signal, instead of dMRI derived measures such as fractional anisotropy) using rotation invariant spherical harmonic (RISH) features embedded within a multi-modal image registration framework. All dMRI data sets from all sites are registered to a common template and voxel-wise differences in RISH features between sites at a group level are used to harmonize the signal in a subject-specific manner. We validate our method on diffusion data acquired from seven different sites (two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across these sites before and after data harmonization. Validation was also done on a group oftest subjects, which were not used to "learn" the harmonization parameters. We also show results using TBSS before and after harmonization for independent validation of the proposed methodology. Using synthetic data, we show that any abnormality in diffusion measures due to disease is preserved during the harmonization process. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences in the signal can be removed using the proposed method in a model independent manner.
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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.