دورية أكاديمية
Example dataset for the hMRI toolbox
العنوان: | Example dataset for the hMRI toolbox |
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المؤلفون: | Callaghan, martina F., Lutti, Antoine, Ashburner, John, Balteau, Evelyne, Corbin, Nadège, Draganski, Bogdan, Helms, Gunther, Kherif, Ferath, Leutritz, Tobias, Mohammadi, Siawoosh, Phillips, Christophe, Reimer, Enrico, Ruthotto, Lars, Seif, Maryam, Tabelow, Karsten, Ziegler, Gabriel, Weiskopf, Nikolaus |
المصدر: | Data in Brief (2019-08) |
بيانات النشر: | Elsevier, 2019. |
سنة النشر: | 2019 |
مصطلحات موضوعية: | hMRI, quantitative MRI, dataset, Physical, chemical, mathematical & earth Sciences, Engineering, computing & technology, Human health sciences, Neurology, Physique, chimie, mathématiques & sciences de la terre, Ingénierie, informatique & technologie, Sciences de la santé humaine, Neurologie |
الوصف: | The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi-parameter mapping (MPM) protocol, incorporating calibration data to correct for spatial variation in the scanner's transmit and receive fields, is the most complete protocol that can be handled by the toolbox. Here we present a dataset acquired with such a full MPM protocol, which is made freely available to be used as a tutorial by following instructions provided on the associated toolbox wiki pages, which can be found at http://hMRI.info, and following the theory described in: hMRI – A toolbox for quantitative MRI in neuroscience and clinical research |
نوع الوثيقة: | journal article http://purl.org/coar/resource_type/c_6501 article |
اللغة: | English |
Relation: | https://www.sciencedirect.com/science/article/pii/S235234091930486X; urn:issn:2352-3409 |
DOI: | 10.1016/j.dib.2019.104132 |
URL الوصول: | https://orbi.uliege.be/handle/2268/238568 |
حقوق: | open access http://purl.org/coar/access_right/c_abf2 info:eu-repo/semantics/openAccess |
رقم الأكسشن: | edsorb.238568 |
قاعدة البيانات: | ORBi |
DOI: | 10.1016/j.dib.2019.104132 |
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