ArticleNeuroImage2020
DeepDTI: High-fidelity six-direction diffusion tensor imaging using deep learning.
Article in NeuroImage, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
54 citing papers in PubMed.
- Joint Reconstruction of Multiple b-Values and Multiple Directions for Accelerating Diffusion Kurtosis Imaging.Magnetic resonance in medicine · 2026Article
- Improved diffusion tensor parametric maps in the brain from reduced-direction acquisitions using a deep learning approach.Magma (New York, N.Y.) · 2026Article
- Four Directions, One Solution: Enabling Rapid Diffusion Tensor MRI for Ultra-Low Field Using Deep Learning.Magnetic resonance in medicine · 2026Article
- Hierarchical Bayesian Modelling Improves Microstructural Parameter Mapping in Diffusion and Exchange MRI Data.NMR in biomedicine · 2026Article
- Image Distortion Correction for Diffusion MR Imaging Using a Transformer-based U-Net.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2026Article
- Gray Matter Morphological Networks are Associated with Neurobiological Features, Cognitive Status and Clinical Recovery in Traumatic Brain Injury.medRxiv : the preprint server for health sciences · 2026Article
- Deep Learning Empowered Microstructure Codebook: New Paradigm for Multi-Parameter Tissue Characterization Estimation.Human brain mapping · 2026Article
- DcSE: an improved densenet with enhanced attention fusion for super-enhancer prediction.BMC genomics · 2026Article
- Discovery of Abundant Nano-scale Lymphatic-like Vessels in Brains.bioRxiv : the preprint server for biology · 2026Article
- Repeatable tract-based diffusion metrics on a portable 64 mT MRI: a foundation for global population neuroscience.Frontiers in neuroimaging · 2026Article
- Synthetic X-Q space learning for diffusion MRI parameter estimation: a pilot study in breast DKI.International journal of computer assisted radiology and surgery · 2025Article
- Deep Learning for fODF Estimation in Infant Brains: Model Comparison, Ground-Truth Impact, and Domain Shift Mitigation.Human brain mapping · 2025Article
- Accelerated multi-shell diffusion MRI with Gaussian process estimated reconstruction of multi-band imaging.Magnetic resonance in medicine · 2025Article
- Accelerated diffusion tensor imaging with self-supervision and fine-tuning.Scientific reports · 2025Article
- Gauge equivariant convolutional neural networks for diffusion MRI.Scientific reports · 2025Article
- Super-resolution mapping of anisotropic tissue structure with diffusion MRI and deep learning.Scientific reports · 2025Article
- Enhancing drug-target interaction prediction with graph representation learning and knowledge-based regularization.Frontiers in bioinformatics · 2025Article
- Harnessing big data for precision medicine: radiomics based application of nanomaterials in MRI enhancement and multimodal therapy of hepatocellular carcinoma.Frontiers in immunology · 2025Review
- EPI-DynFusion: enhancer-promoter interaction prediction model based on sequence features and dynamic fusion mechanisms.Frontiers in genetics · 2025Article
- Blip-up blip-down circular EPI (BUDA-cEPI) for distortion-free dMRI with rapid unrolled deep learning reconstruction.Magnetic resonance imaging · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Diffusion tensor magnetic resonance imaging (DTI) is unsurpassed in its ability to map tissue microstructure and structural connectivity in the living human brain. Nonetheless, the angular sampling requirement for DTI leads to long scan times and poses a critical barrier to performing high-quality DTI in routine clinical practice and large-scale research studies. In this work we present a new processing framework for DTI entitled DeepDTI that minimizes the data requirement of DTI to six diffusion-weighted images (DWIs) required by conventional voxel-wise fitting methods for deriving the six unique unknowns in a diffusion tensor using data-driven supervised deep learning. DeepDTI maps the input non-diffusion-weighted (b = 0) image and six DWI volumes sampled along optimized diffusion-encoding directions, along with T
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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.