{"pubs":[{"_id":"675af884becd6464d43296c5","user_id":"41","license":"ccby.40","fundings":[],"project":"6554f423b094062da63aa4c9","authors":["41","2022","1941","2998","2829"],"contributors":[],"name":"A labeled Clinical-MRI dataset of Nigerian brains","desc":"This dataset contains pseudonymized structural MRI (T1w, T2w, FLAIR) data of clinical quality, with 35 images from healthy control subjects, 31 images from individuals diagnosed with age-related dementia, and 22 from individuals with Parkinson's Disease.","tags":["MRI","FLAIR","T1w","T2w","dementia","Parkinson"],"readme":"There is currently a paucity of neuroimaging data from the African continent, limiting the diversity of data from a significant proportion of the global population. This in turn diminishes global health research and innovation. To address this issue, we present and describe the first Magnetic Resonance Imaging (MRI) dataset from individuals in the African nation of Nigeria. This dataset contains pseudonymized structural MRI (T1w, T2w, FLAIR) data of clinical quality, with 35 images from healthy control subjects, 31 images from individuals diagnosed with age-related dementia, and 22 from individuals with Parkinson's Disease. Given the potential for Africa to contribute to the global neuroscience community, this unique MRI dataset represents both an opportunity and benchmark for future studies to share data from the African continent.\n\nAuthors\nEberechi Wogu1*, Patrick Filima1*, Bradley Caron2#, Daniel Deabler2#, Peer Herholz2, Catherine Leal2, Mohammed F. Mehboob2, Sohmee Kim2, Ananya Gosain2, Alisha Flexwala2, Soichi Hayashi3, Simisola Akintoye4, George Ogoh5, Tawe Godwin6, Damian Eke4, Franco Pestilli2 \n\nAffiliations\n1.\tUniversity of Port Harcourt, Choba, Rivers State, Nigeria.\n2.\tDepartment of Psychology, Department of Neuroscience, Center for Perceptual Systems, Center for Learning and Memory, The University of Texas at Austin, Austin, TX, USA\n3. \tIndiana University, Bloomington, Indiana, USA\n4.\tCenter for Law, Justice and Society, De Montfort University, UK.\n5.\tSchool of Computing, University of Nottingham, UK.\n6.\tLifeBridge Medical Diagnostic Center, Garki 2, Abuja Nigeria.\n\t\n*,# These authors contributed equally to this work\n\nThis data was preprocessed using [ezBIDS](https://brainlife.io/ezbids) version 1.0.0. This dataset conforms to version 1.8.0 of the BIDS Specification.\nThe data were pseudonymized using [QuickShear](https://github.com/nipy/quickshear). ","releases":[{"name":"1","create_date":"2024-12-12T00:00:00.000Z","removed":false,"subjects":88,"sessions":4,"sets":[{"datatype":{"_id":"5d9cf81c0eed545f51bf75df","name":"neuro/anat/flair","desc":"Fluid Attenuated Inversion Recovery (flair). The Flair sequence is similar to a T2-weighted image except that the TE and TR times are very long. By doing so, abnormalities remain bright but normal CSF fluid is attenuated and made dark. This sequence is very sensitive to pathology and makes the differentiation between CSF and an abnormality much easier.","groupAnalysis":false},"datatype_tags":[],"tags":[],"subjects":[],"size":518707200,"count":114,"_id":"675af884becd6464d43296c7"},{"datatype":{"_id":"594c0325fa1d2e5a1f0beda5","name":"neuro/anat/t2w","desc":"T2 weighted","groupAnalysis":false},"datatype_tags":[],"tags":[],"subjects":[],"size":746076160,"count":205,"_id":"675af884becd6464d43296c8"},{"datatype":{"_id":"58c33bcee13a50849b25879a","name":"neuro/anat/t1w","desc":"T1-weighted magnetic resonance data (MRI), saved in NIfTI-1 format.","groupAnalysis":false},"datatype_tags":[],"tags":[],"subjects":[],"size":1990205440,"count":442,"_id":"675af884becd6464d43296c9"},{"datatype":{"_id":"58c33c5fe13a50849b25879b","name":"neuro/dwi","desc":"Diffusion-weighted magnetic resonance data (dMRI), saved in NIfTI-1 format.","groupAnalysis":false},"datatype_tags":[],"tags":[],"subjects":[],"size":81530880,"count":26,"_id":"675af884becd6464d43296ca"}],"apps":[],"gaarchives":[],"_id":"675af884becd6464d43296c6"}],"removed":false,"create_date":"2024-12-12T14:51:48.362Z","relatedPapers":[],"doi":"10.25663/brainlife.pub.61","__v":4}],"count":1}