Nighres: processing tools for high-resolution neuroimaging
Autor: | Pierre-Louis Bazin, Julia M. Huntenburg, Christopher J. Steele |
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Přispěvatelé: | Brain and Cognition, Brein en Cognitie (Psychologie, FMG), Psychology Other Research (FMG), Netherlands Institute for Neuroscience (NIN), Spinoza Centre for Neuroimaging |
Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
0301 basic medicine
Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Health Informatics Image processing Machine learning computer.software_genre Online Systems 03 medical and health sciences 0302 clinical medicine Documentation Software Neuroimaging Computer Systems Journal Article Image Processing Computer-Assisted Technical Note Humans Segmentation Image resolution computer.programming_language Brain Mapping business.industry laminar MRI python Java integration Brain ultra-high field MRI Python (programming language) Magnetic Resonance Imaging Toolbox Computer Science Applications 030104 developmental biology high-resolution MRI Programming Languages Artificial intelligence business computer neuroimaging in python 030217 neurology & neurosurgery Algorithms Medical Informatics |
Zdroj: | GigaScience, 7(7):giy082. Oxford University Press GigaScience GigaScience, 7:giy082. BioMed Central |
ISSN: | 2047-217X |
Popis: | With recent improvements in human magnetic resonance imaging (MRI) at ultra-high fields, the amount of data collected per subject in a given MRI experiment has increased considerably. Standard image processing packages are often challenged by the size of these data. Dedicated methods are needed to leverage their extraordinary spatial resolution. Here, we introduce a flexible Python toolbox that implements a set of advanced techniques for high-resolution neuroimaging. With these tools, segmentation and laminar analysis of cortical MRI data can be performed at resolutions up to 500 μm in reasonable times. Comprehensive online documentation makes the toolbox easy to use and install. An extensive developer's guide encourages contributions from other researchers that will help to accelerate progress in the promising field of high-resolution neuroimaging. |
Databáze: | OpenAIRE |
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