ArticleMedical image analysis2018
Estimating fiber orientation distribution from diffusion MRI with spherical needlets.
Article in Medical image analysis, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- DeepFixel: Crossing white matter fiber identification through spherical convolutional neural networks.Proceedings of SPIE--the International Society for Optical Engineering · 2026Article
- ESTIMATING FIBER ORIENTATION DISTRIBUTION WITH APPLICATION TO STUDY BRAIN LATERALIZATION USING HCP D-MRI DATA.The annals of applied statistics · 2024Article
- Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging-Tractography in Resective Brain Surgery: Lesion Coverage Strategies and Patient Outcomes.Brain sciences · 2023Article
- Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data.Information processing in medical imaging : proceedings of the ... conference · 2021Article
- Three-dimensional collagen fiber mapping and tractography of human uterine tissue using OCT.Biomedical optics express · 2020Article
- High-speed collagen fiber modeling and orientation quantification for optical coherence tomography imaging.Optics express · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
We present a novel method for estimation of the fiber orientation distribution (FOD) function based on diffusion-weighted magnetic resonance imaging (D-MRI) data. We formulate the problem of FOD estimation as a regression problem through spherical deconvolution and a sparse representation of the FOD by a spherical needlets basis that forms a multi-resolution tight frame for spherical functions. This sparse representation allows us to estimate the FOD by ℓ
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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.