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brain imaging data structure (bids) format using the ku leuven neuroimaging suite (kul_nis)  (KU Leuven)

 
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    KU Leuven brain imaging data structure (bids) format using the ku leuven neuroimaging suite (kul_nis)
    Summarized demographics, pathological type, distribution, and volumes.
    Brain Imaging Data Structure (Bids) Format Using The Ku Leuven Neuroimaging Suite (Kul Nis), supplied by KU Leuven, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/brain+imaging+data+structure/brain+imaging+data+structure++bids++format+using+the+ku+leuven+neuroimaging+suite++kul+nis+/pmc11033921-93-21-25
    Average 90 stars, based on 1 article reviews
    brain imaging data structure (bids) format using the ku leuven neuroimaging suite (kul_nis) - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation"

    Article Title: Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation

    Journal: Human Brain Mapping

    doi: 10.1002/hbm.26662

    Summarized demographics, pathological type, distribution, and volumes.
    Figure Legend Snippet: Summarized demographics, pathological type, distribution, and volumes.

    Techniques Used:

    Schematic representation of the data preprocessing and analysis workflow used to compare different tractography results to intraoperative mapping outcome. BIDS, brain imaging data structure; DSC, dice similarity coefficient; DTI, diffusion tensor imaging; FACT, fiber assignment by continuous tracking; JI, Jaccard index; KUL_FWT, KU Leuven fun with tracts; KUL_NIS, KU Leuven neuroimaging suite; KUL_VBG, KU Leuven virtual brain grafting; MRI, magnetic resonance imaging.
    Figure Legend Snippet: Schematic representation of the data preprocessing and analysis workflow used to compare different tractography results to intraoperative mapping outcome. BIDS, brain imaging data structure; DSC, dice similarity coefficient; DTI, diffusion tensor imaging; FACT, fiber assignment by continuous tracking; JI, Jaccard index; KUL_FWT, KU Leuven fun with tracts; KUL_NIS, KU Leuven neuroimaging suite; KUL_VBG, KU Leuven virtual brain grafting; MRI, magnetic resonance imaging.

    Techniques Used: Imaging, Diffusion-based Assay, Magnetic Resonance Imaging



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    Image Search Results


    Summarized demographics, pathological type, distribution, and volumes.

    Journal: Human Brain Mapping

    Article Title: Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation

    doi: 10.1002/hbm.26662

    Figure Lengend Snippet: Summarized demographics, pathological type, distribution, and volumes.

    Article Snippet: All acquired images were converted to the brain imaging data structure (BIDS) (Gorgolewski et al., ) format using the KU Leuven Neuroimaging suite (KUL_NIS) ( KULeuven Neuro Imaging Suite (KUL_NIS) , 2018/ ) ( https://github.com/treanus/KUL_NIS ) and dcm2bids (Bedetti et al., ).

    Techniques:

    Schematic representation of the data preprocessing and analysis workflow used to compare different tractography results to intraoperative mapping outcome. BIDS, brain imaging data structure; DSC, dice similarity coefficient; DTI, diffusion tensor imaging; FACT, fiber assignment by continuous tracking; JI, Jaccard index; KUL_FWT, KU Leuven fun with tracts; KUL_NIS, KU Leuven neuroimaging suite; KUL_VBG, KU Leuven virtual brain grafting; MRI, magnetic resonance imaging.

    Journal: Human Brain Mapping

    Article Title: Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation

    doi: 10.1002/hbm.26662

    Figure Lengend Snippet: Schematic representation of the data preprocessing and analysis workflow used to compare different tractography results to intraoperative mapping outcome. BIDS, brain imaging data structure; DSC, dice similarity coefficient; DTI, diffusion tensor imaging; FACT, fiber assignment by continuous tracking; JI, Jaccard index; KUL_FWT, KU Leuven fun with tracts; KUL_NIS, KU Leuven neuroimaging suite; KUL_VBG, KU Leuven virtual brain grafting; MRI, magnetic resonance imaging.

    Article Snippet: All acquired images were converted to the brain imaging data structure (BIDS) (Gorgolewski et al., ) format using the KU Leuven Neuroimaging suite (KUL_NIS) ( KULeuven Neuro Imaging Suite (KUL_NIS) , 2018/ ) ( https://github.com/treanus/KUL_NIS ) and dcm2bids (Bedetti et al., ).

    Techniques: Imaging, Diffusion-based Assay, Magnetic Resonance Imaging

    State of population of selected  data  repositories 2014 vs. 2023.

    Journal: Frontiers in Neuroinformatics

    Article Title: The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR

    doi: 10.3389/fninf.2023.1276407

    Figure Lengend Snippet: State of population of selected data repositories 2014 vs. 2023.

    Article Snippet: The INCF was created to help with this process of standardization and produced some early successes, e.g., the Waxholm space for registration of mouse and rat brain data ( ; ), the Neuroimaging Data Model ( ) the Brain Imaging Data Structure ( ) were produced with support from INCF.

    Techniques: Imaging, Functional Assay, Optical Imaging, Electron Microscopy

    Journal: Frontiers in Neuroinformatics

    Article Title: The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR

    doi: 10.3389/fninf.2023.1276407

    Figure Lengend Snippet:

    Article Snippet: The INCF was created to help with this process of standardization and produced some early successes, e.g., the Waxholm space for registration of mouse and rat brain data ( ; ), the Neuroimaging Data Model ( ) the Brain Imaging Data Structure ( ) were produced with support from INCF.

    Techniques: Microscopy, Imaging, Computed Tomography, Functional Assay, Magnetic Resonance Imaging, Positron Emission Tomography, Activity Assay, Single Photon Emission Computed Tomography