ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2020
Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging.
Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- A multimodal submillimeter MRI atlas of the human cerebellum.Scientific reports · 2024Article
- Microstructure Fingerprinting for Heterogeneously Oriented Tissue Microenvironments.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2023Article
- Probing Tissue Microarchitecture of the Baby Brain via Spherical Mean Spectrum Imaging.IEEE transactions on medical imaging · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Most brain microstructure models are dedicated to the quantification of white matter microstructure, using for example sticks, cylinders, and zeppelins to model intra- and extra-axonal environments. Gray matter presents unique micro-architecture with cell bodies (somas) exhibiting diffusion characteristics that differ from axons in white matter. In this paper, we introduce a method to quantify soma microstructure, giving measures such as volume fraction, diffusivity, and kurtosis. Our method captures a spectrum of diffusion patterns and scales and does not rely on restrictive model assumptions. We show that our method yields unique and meaningful contrasts that are in agreement with histological data. We demonstrate its application in the mapping of the distinct spatial patterns of soma density in the cortex.
Identifiers
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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.