• español
  • English
  • français
  • Deutsch
  • português (Brasil)
  • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Ricerca

    Tutto UVaDOCArchiviData di pubblicazioneAutoriSoggettiTitoli

    My Account

    Login

    Estadísticas

    Ver Estadísticas de uso

    Compartir

    Mostra Item 
    •   UVaDOC Home
    • PRODUZIONE SCIENTIFICA
    • Departamentos
    • Dpto. Teoría de la Señal y Comunicaciones e Ingeniería Telemática
    • DEP71 - Artículos de revista
    • Mostra Item
    •   UVaDOC Home
    • PRODUZIONE SCIENTIFICA
    • Departamentos
    • Dpto. Teoría de la Señal y Comunicaciones e Ingeniería Telemática
    • DEP71 - Artículos de revista
    • Mostra Item
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano

    Exportar

    RISMendeleyRefworksZotero
    • edm
    • marc
    • xoai
    • qdc
    • ore
    • ese
    • dim
    • uketd_dc
    • oai_dc
    • etdms
    • rdf
    • mods
    • mets
    • didl
    • premis

    Citas

    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/52106

    Título
    Anisotropy measure from three diffusion-encoding gradient directions
    Autor
    Aja Fernández, SantiagoAutoridad UVA Orcid
    París Brandés, Guillem Lluis
    Martín Martín, CarmenAutoridad UVA
    Jones, Derek K.
    Tristán Vega, AntonioAutoridad UVA Orcid
    Año del Documento
    2022
    Editorial
    Elsevier
    Descripción
    Producción Científica
    Documento Fuente
    Magnetic Resonance Imaging, 2022, vol. 88. p. 38-43
    Abstract
    We propose a method that can provide information about the anisotropy and orientation of diffusion in the brain from only 3 orthogonal gradient directions without imposing additional assumptions. The method is based on the Diffusion Anisotropy (DiA) that measures the distance from a diffusion signal to its isotropic equivalent. The original formulation based on a Spherical Harmonics basis allows to go down to only 3 orthogonal directions in order to estimate the measure. In addition, an alternative simplification and a color-coding representation are also proposed. Acquisitions from a publicly available database are used to test the viability of the proposal. The DiA succeeded in providing anisotropy information from the white matter using only 3 diffusion-encoding directions. The price to pay for such reduced acquisition is an increment in the variability of the data and a subestimation of the metric on those tracts not aligned with the acquired directions. Nevertheless, the calculation of anisotropy information from DMRI is feasible using fewer than 6 gradient directions by using DiA. The method is totally compatible with existing acquisition protocols, and it may provide complementary information about orientation in fast diffusion acquisitions.
    Palabras Clave
    Anisotropy
    Anisotropía
    Brain
    Cerebro
    ISSN
    0730-725X
    Revisión por pares
    SI
    DOI
    10.1016/j.mri.2022.01.014
    Patrocinador
    Ministerio de Ciencia e Innovación (grant RTI2018-094569-B-I00)
    Wellcome Trust Investigator Award (award 096646/Z/11/Z)
    Wellcome Trust Strategic Award (award 104943/Z/14/Z)
    Version del Editor
    https://www.sciencedirect.com/science/article/pii/S0730725X22000145?via%3Dihub
    Propietario de los Derechos
    © 2022 The Authors
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/52106
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP71 - Artículos de revista [358]
    Mostra tutti i dati dell'item
    Files in questo item
    Nombre:
    Anisotropy-measure.pdf
    Tamaño:
    2.656Mb
    Formato:
    Adobe PDF
    Thumbnail
    Mostra/Apri
    Attribution-NonCommercial-NoDerivatives 4.0 InternacionalLa licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 Internacional

    Universidad de Valladolid

    Powered by MIT's. DSpace software, Version 5.10