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309 results for “brain MRI”
Figures a, b ,c -8-An Optimized Clustering Approach for Automated Detection of White Matter Lesions in MRI Brain Images
<p>In turn, the optimized results of<br> GFCM provide overall accuracy of 95%. Figures 8(a), 8(b) and 8(c) shows the comparison results<br> of clustering models and optimization technique in terms of Se, Sp and Acc.</p>
An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain for Automated Anatomical Segmentation
<p>This version of the dataset described in: <a href="https://www.biorxiv.org/content/10.1101/743583v2">https://www.biorxiv.org/content/10.1101/743583v2</a>, is outdated. Please refer to https://doi.org/10.5281/zenodo.3555556 for the current version and all future editions of the Fischer 344 neuroanatomical atlas.</p>
Validation of the registration of intraoperative optical image of exposed brain with preoperative MRI volumes (T1 volumes with injection of Gadolinium).
<p>This dataset contains the results of the registration of intraoperative optical images of exposed brain with pre-operative MRI volumes (T1 volumes with injection of Gadolinium). The file contains the validation metric (Euclidean distance) calculated with a landmark-based validation approach for 9 patients.</p>
Impact of prenatal THC exposure on mouse brain development; a lifespan approach with MRI
<p>Prenatal cannabis exposure has been demonstrated to impact neurodevelopment in offspring at different ages. To date, to our knowledge, no study has longitudinally examined the effects from embryos to adulthood. Here we collected and analyzed data to explore how prenatal exposure to delta-9-tetrahydrocannabinol (5 mg/kg subcutaneous injections, gestational dat [GD] 3-10) in mice impacts trajectories of brain development with structural magnetic resonance imaging. We supplement these findings with behavioural analyses and electron microscopy as described below.</p> <p>In the first cohort (embryos) embryos were extracted on GD 17 and scanned with MRI postnatally, as described in the methods of the accompanying paper. Electron microscopy was used to investigate dark neural and glial cells, apoptotic cells, and dividing cells in the hippocampus. In the second cohort (neonates) pups were born and scanned postnatally with manganese enhanced MRI on postnatal day (PND) 3, 5, 7, and 10. Separation-induced ultrasonic vocalizations were acquired on PND 12 and pups were perfused on PND 13. EM analyses were repeated in the neonatal hippocampi. In the third cohort (adults) pups were scanned on PND 25, 35, 60, and 90. Behavioral assessments for anxiety-like behavior with open-field test and sensorimotor gating with prepulse inhibition were performed on PND 35 and 37 respectively. </p> <p>Findings showed altered prenatal body volumes and weight-trajectories, altered brain volumes (especially sustained in females until adulthood), and indications of changes to behavior, including anxiety-like phenotypes in neonates and adolescents. Evidence from electron microscopy suggests increased cell division in the embryo hippocampus. Together these data suggest a profound and sustained impact of early gestation prenatal THC exposure on brain development. For further details on the methods, approach, and results, please see the forthcoming publication.</p> <p>In this dataset you will find the following data:</p> <p>Pregnancy/dam-level outcomes can be found in maternal_outcomes.zip</p> <ul> <li><a href="../api/records/13820978/draft/files/zenodo_pregnancy_README.txt/content" target="_blank" rel="noopener noreferrer">zenodo_pregnancy_README.txt</a>: includes description of the data and fields available in each csv.</li> <li>dam_weights.csv: A spreadsheet including the information related to each dam pooled across the studies</li> <li>nest_quality.csv: A spreadsheet including the manually-rated nest quality from a pilot and the full experiment</li> <li>master_maternal_observations_old_thc.csv: A spreadsheet including data for time spent on and off nest extracted automatically and manually from Ethovision</li> </ul> <p>Embryo outcomes:</p> <ul> <li>zenodo_embryos_README.txt: includes description of the data and fields available in each csv.</li> <li>demographics_for_analysis.csv: A spreadsheet with relevant information for each embryo sample.</li> <li>raw_embryo_mincs.zip: includes 84 embryo scans, full body</li> <li>embryo_heads.zip: includes 57 embryo scans that all passed qc, head only niftis </li> <li>squish_qc.csv: QC of whether the embryos were squished or not</li> <li>em_embryo_hc_mm2csv.csv: cells per mm^2 from electron microscopy</li> </ul> <p>Neonate outcomes:</p> <ul> <li>zenodo_neonates_README.txt: includes description of data and fields available in each csv</li> <li>demographics.csv: A spreadsheet with the demographic information for each pup and timepoint in the study</li> <li>raw_neonate_niftis.zip: 172 scans from neonates in nifti format</li> <li>agreement_qc.csv: quality control file with assessments of raw images</li> <li>milestones_999_as_NA.csv: Record of which milestones were tested and whether they were obtained</li> <li>master_usv.csv: Spreadsheet including data for ultrasonic vocalizations from all tested pups</li> <li>neo_cell_counts_mm2.csv: cells per mm^2 from electron microscopy for the neonates</li> </ul> <p>Adult outcomes: </p> <ul> <li>zenodo_adult_README.txt: includes description of the data and fields available in each csv.</li> <li>demographics.csv: A spreadsheet with the demographic information for each mouse and timepoint in the study</li> <li>adult_raw_niftis.zip: The raw data (before preprocessing) in nifti format</li> <li>master_qc.csv: Quality control assessment of the raw images</li> <li>master_oft.csv: Values for open field test extracted from Ethovision</li> <li>avg_trials_ppi.csv: Data from prepulse inhibition trials, average startle of 100 ms following pulse</li> <li>max_trials_ppi.csv Dat afrom prepulse inhibition trials, maximum startle of 100 ms following pulse</li> </ul>
Simultaneous dynamic glucose-enhanced (DGE) MRI and fiber photometry measurements of glucose in the healthy mouse brain
<p>This dataset was acquired for the DGE and fiber photometry study published in NeuroImage ( <a href="https://doi.org/10.1016/j.neuroimage.2022.119762">https://doi.org/10.1016/j.neuroimage.2022.119762</a>).<br> Comprises of three datasets: DGE MRI, fiber photometry and two-photon microscopy.</p>
Example meshes for 'Human brain solute transport quantified by glymphatic MRI-informed biophysics during sleep and sleep deprivation'
<p>Example meshes for 'Human brain solute transport quantified by glymphatic MRI-informed biophysics during sleep and sleep deprivation'</p> <p>The meshes contain DTI. To read the mesh to FEniCS, see e.g., <a href="https://github.com/bzapf/braintransport/blob/24ba4e37a3d6fadb37c249ca7f717a7355f48f30/optimal_velocity/postprocess_phi.py#L12">here </a>.</p> <p>Find the simulation codes for the manuscript here:</p> <p><a href="https://github.com/bzapf/braintransport">https://github.com/bzapf/braintransport</a></p>
Investigation of Brain Functional MRI as an Early Biomarker of Recovery in Individuals With Spinal Cord Injury
ClinicalTrials.gov study NCT03854214. IPD Sharing: YES. Countries: 1. Publications: 4.
Data from: Direct segmentation of cortical cytoarchitectonic domains using ultra-high-resolution whole-brain diffusion MRI
Open the record for dataset details and reuse information.
Data from: The MRi-Share database: Brain imaging in a cross-sectional cohort of 1,870 university students
Open the record for dataset details and reuse information.
T1-Weighted MRI of a crow brain
<p>T1-Weighted MRI of a brain from a wild American crow that has been coregistered and scaled to the jungle crow atlas: http://carls.keio.ac.jp/bird_brain/bird_brain.html</p>
Longitudinal stability of brain and spinal cord quantitative MRI measures
<p><strong>About: </strong>Tabular (CSV) files are generated by the Courtois Neuromod<a href="https://github.com/courtois-neuromod/anat-processing"> structural data processing workflow</a>. These files contain quantitative MRI metrics such as T1, MTsat, and MTR, in addition to fundamental diffusion tensor imaging indices like RD and FA derived from brain data. The results also encompass the same metrics for spinal cord imaging data, supplemented with additional metrics for spinal cord morphometry. For details regarding the raw data please visit <a href="https://www.cneuromod.ca">https://www.cneuromod.ca</a>. </p><p>Dataset provided for NeuroLibre preprint. Author repo: https://github.com/courtois-neuromod/anat-processing-paper NeuroLibre fork:https://github.com/roboneurolibre/anat-processing-paper</p><p>For details, please visit the corresponding <a href="https://github.com/neurolibre/neurolibre-reviews/issues/18">NeuroLibre technical screening.</a></p><p><a href="https://neurolibre.org"><strong>https://neurolibre.org</strong></a></p>
[Dataset for] Whole-brain meso-vein imaging in living humans using fast 7 T MRI
<p>This dataset is associated with:</p> <ul> <li>Gulban, Stirnberg, Tse, Pizzuti, Koiso, Archila-Melendez, Huber, Bollmann, Goebel, Kay, Ivanov, 2025. Whole-brain meso-vein imaging in living humans using fast 7 T MRI (Preprint).</li> </ul> <p>This dataset is also used in:</p> <ul> <li>Pizzuti, Bazin, Ivanov, Dresbach, Peter, Goebel, Gulban, 2024. Multimodal laminar characterization of visual areas along the cortical hierarchy (Preprint).</li> </ul> <p>More data are going to be be added as we progress with our manuscripts though their publications or upon request (please contact Omer Faruk Gulban).</p>
Ultra-high-resolution diffusion MRI atlas of CD1 embryonic mouse brains at E10.5-E15.5.
<p>This dataset is assciated with the paper "A Spatiotemporal Continuum of Embryonic Mouse Brain Development Built on Diffusion MR Microscopy for Probing Dynamic Gene-Neuroanatomy" on PNAS. For each stage, average FA (fractional anisotropy) and DEC (directionally encoded colormap) images (n=5) are provided. <br> <br> </p>
Data from: In vivo human whole-brain Connectom diffusion MRI dataset at 760 µm isotropic resolution (PART I)
<p>This whole-brain in vivo diffusion MRI dataset was acquired at 760 µm isotropic resolution and sampled at 1260 q-space points across 9 two-hour sessions on a single healthy subject. It was acquired using state-of-the-art acquisition hardware and advanced reconstruction to achieve high SNR at such resolution, including a high-gradient-strength Connectom scanner, a custom-built 64-channel phased-array coil, a personalized motion-robust head stabilizer, a recently developed SNR-efficient dMRI acquisition, and parallel imaging reconstruction with advanced ghost reduction algorithms. With its unprecedented high resolution, SNR and image quality, it could help explore the fine-scale structures of in vivo human brain, and further advance the understanding of human brain connectivity. This dataset can also be used as a test bed for further technical development of new modeling, sub-sampling strategies, denoising and processing algorithms for in vivo high resolution dMRI. Whole brain anatomical T<sub>1</sub>-weighted and T<sub>2</sub>-weighted images at submillimeter scale, field maps and the code for preprocessing pipeline are also made available in the repository.</p>
Multi-contrast MRI and histology datasets used to train and validate MRH networks to generate virtual mouse brain histology
<p><span>H MRI maps brain structure and function non-invasively through versatile contrasts that exploit inhomogeneity in tissue micro-environments. Inferring histopathological information from MRI findings, however, remains challenging due to absence of direct links between MRI signals and cellular structures. Here, we provided deep convolutional neural networks, called MRH-Nets, developed using co-registered multi-contrast MRI and histological data of the mouse brain, can estimate histological staining intensity directly from MRI signals at each voxel. The results provide three-dimensional maps of axons and myelin with tissue contrasts that closely mimics target histology and enhanced sensitivity and specificity compared to conventional MRI markers. </span><span> </span>The dataset contains multi-contrast MRI and histology used for the training and testing and the acquisition parameters. The datasets have been carefully registered to mouse brain images from the Allen Mouse Brain Atlas (https://mouse.brain-map.org). The source codes for MRH-Nets can be found at <a href="https://github.com/liangzifei/MRH-Net">https://github.com/liangzifei/MRH-Net</a>.</p>
Data from: Changes in brain structure and function following exposure to oral LSD during adolescence: A multimodal MRI study
<p><em>Background</em>: LSD is a hallucinogen with complex neurobiological and behavioral effects. Underlying these effects are changes in brain neuroplasticity. This is the first study to follow the developmental changes in brain structure and function following LSD exposure in periadolescence. We hypothesized LSD given during a time of heightened neuroplasticity, particularly in the forebrain, would affect cognitive and emotional behavior and the associated underlying neuroanatomy and neurocircuitry. </p> <p><em>Methods:</em> Female and male mice were given vehicle, single, or multiple treatments of 3.3 µg of LSD by oral gavage starting on postnatal day 51. Between postnatal days 90-120 mice were imaged and tested for cognitive and motor behavior. MRI data from voxel-based morphometry, diffusion weighted imaging, and BOLD resting state functional connectivity were registered to a mouse 3D MRI atlas with 139 brain regions providing site-specific differences in global brain structure and functional connectivity between experimental groups.</p> <p><em>Results:</em> Motor behavior and cognitive performance were unaffected by periadolescent exposure to LSD. Differences across experimental groups in brain volume for any of the 139 brain areas were few in number and not focused on any specific brain region. Multiple exposures to LSD significantly altered gray matter microarchitecture across much of the brain. These changes were primary associated with the thalamus, sensory and motor cortices, and basal ganglia. The forebrain olfactory system and prefrontal cortex and hindbrain cerebellum and brainstem were unaffected. The functional connectivity between forebrain white matter tracts and sensorimotor cortices and hippocampus was reduced with multidose LSD exposure.</p> <p><em>Conclusion:</em> Does early exposure to LSD in periadolescence have lasting effects on brain development? There was no evidence of LSD having consequential effects on cognitive or motor behavior when animal were evaluated as young adults 90-120 days of age. Neither were there any differences in the volume of specific brain areas between experimental conditions. The pronounced changes in indices of anisotropy across much of the brain would suggest altered gray matter microarchitecture and neuroplasticity. The reduction in connectivity in forebrain white matter tracts with multidose LSD and consolidation around sensorimotor and hippocampal brain areas requires a battery of tests to understand the consequences of these changes on behavior.</p>
Data pertaining to the published article "Detection of pathological contrast enhancement with synthetic brain imaging from quantitative multiparametric MRI" by Donatelli et al., 2024
<p>Data pertaining to the published article "Detection of pathological contrast enhancement with synthetic brain imaging from quantitative multiparametric MRI" by Donatelli et al., 2024. <a href="https://doi.org/10.1111/jon.13201">https://doi.org/10.1111/jon.13201</a></p>
brain-tumor-mri-dataset
<p>Brain Tumor MRI Dataset from Kaggle: https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset</p> <p>Author: Msoud Nickparvar</p>
Linear Registration of brain MRI using knowledge-based multiple intermediator libraries
<p>These are the dataset materials, including full data, resampled data, transformation matrices, experimental results and quantitative evaluation for the paper “Linear Registration of brain MRI using knowledge-based multiple intermediator libraries” that is submitted on the Journal of "Frontiers in Neuroscience".</p>
Data from: Structural and functional brain connectome in motor neuron diseases: a multicenter MRI study
Objective. To investigate structural and functional neural organization in amyotrophic lateral sclerosis (ALS), primary lateral sclerosis (PLS) and progressive muscular atrophy (PMA) patients. Methods. 173 ALS, 38 PLS, 28 PMA sporadic patients and 79 healthy controls were recruited from three Italian centers. Subjects underwent clinical, neuropsychological and brain MRI evaluations. Using graph analysis and connectomics, global and lobar topological network properties and regional structural and functional brain connectivity were assessed. The association between structural and functional network organization and clinical/cognitive data was investigated. Results. Compared to healthy controls, ALS and PLS patients showed altered structural global network properties, as well as local topological alterations and decreased structural connectivity in sensorimotor, basal ganglia, frontal and parietal areas. PMA patients showed preserved global structure. Patient groups did not show significant alterations of functional network topological properties relative to controls. Increased local functional connectivity was observed in ALS patients in the precentral, middle and superior frontal areas, and in PLS patients in the sensorimotor, basal ganglia and temporal networks. In both ALS and PLS patients, structural connectivity alterations correlated with motor impairment, while functional connectivity disruption was closely related to executive dysfunctions and behavioral disturbances. Conclusions. This multicenter study showed widespread motor/extra-motor network degeneration in ALS and PLS, suggesting that graph analysis and connectomics might represent a powerful approach to detect upper motor neuron degeneration, extra-motor brain changes and network reorganization associated with the disease. Network-based advanced MRI provides an objective in vivo assessment of motor neuron diseases, delivering potential prognostic markers.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.