…All simuations based on BrainWeb dataset. The image simulation either taken from Georg Schramm's BrainWeb simulation in 2D, or in 3D it was simulated using BrainWeb package.
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…In brief, the dataset was derived from brain sections of a model for HIV-induced brain injury (HIVgp120tg), which expresses soluble gp120 envelope protein in astrocytes under the control of a modified Brain sections were obtained using a vibratome (Leica VT1000S, Leica Biosystems, Buffalo Grove, IL) and cerebral cortex in 40 μm thick sagittal sections spaced 320 μm apart medial to lateral from brains
…This paper describes a dataset of brain and pelvis computed tomography (CT) images with rigidly registered cone-beam CT (CBCT) and magnetic resonance imaging (MRI) images to facilitate the development Acquisition and Validation Methods The dataset consists of CT, CBCT, and MRI of 540 brains and 540 pelvic radiotherapy patients from three Dutch university medical centers.
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MTNeuro is a multi-task neuroimaging benchmark built on volumetric, micrometer-resolution X-ray microtomography images spanning a large thalamocortical section of mouse brain, encompassing multiple cortical This dataset provides some key features for the neuroinformatics processing community: Three Dimensional Multi-Scale Annotated Dataset: The 3D x-ray microtomography dataset spans multiple brain areas
…During such presurgical evaluation, neurologists try to see if a specific part of the brain is causing the seizures, and if so, if that part of the brain can be removed during surgery.
…The goal of the challenge is to segment two key brain structures involved in the follow-up and treatment planning of vestibular schwannoma (VS): the VS and the cochleas.
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✔️Abstract A Brain tumor is considered as one of the aggressive diseases, among children and adults. Brain tumors account for 85 to 90 percent of all primary Central Nervous System (CNS) tumors. Every year, around 11,700 people are diagnosed with a brain tumor. The 5-year survival rate for people with a cancerous brain or CNS tumor is approximately 34 percent for men and36 percent for women. Brain Tumors are classified as: Benign Tumor, Malignant Tumor, Pituitary Tumor, etc. ✔️ Context Brain Tumors are complex. There are a lot of abnormalities in the sizes and location of the brain tumor(s). Folder Description Yes The folder yes contains 1500 Brain MRI Images that are tumorous No The folder no contains 1500 Brain MRI Images that are non-tumorous By: Ahmed Hamada
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…It is used for 3D axon instance segmentation of brain cortical regions.
This brain anatomy segmentation dataset has 1300 2D US scans for training and 329 for testing.
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…Specifically, it contains data for the following body organs or parts: Brain, Heart, Liver, Hippocampus, Prostate, Lung, Pancreas, Hepatic Vessel, Spleen and Colon.
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The provided dataset consists of high-quality realistic head models and combined EEG/MEG data which can be used for state-of-the-art methods in brain research, such as modern finite element methods (FEM
…We recommend to use Multi Atlas Segmentation and Morphometric analysis toolkit (MASMAT) for mouse brain MRI along with other mouse brain atlases in this repo.
Mindboggle is a large publicly available dataset of manually labeled brain MRI. It consists of 101 subjects collected from different sites, with cortical meshes varying from 102K to 185K vertices. Each brain surface contains 25 or 31 manually labeled parcels.
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Mouse Brain MRI atlas (both in-vivo and ex-vivo) (repository relocated from the original webpage) List of atlases FVB_NCrl: Brain MRI atlas of the wild-type FVB_NCrl mouse strain (used as the background NeAt: Brain MRI atlas of the whld-type C57BL/6J mouse strain. Atlas was created based on the original MRM NeAt mouse brain atlas (template images reoriented and bias-corrected, left/right structure label seperated, and 4th ventricle manual segmentation added). Citation If you use the segmented brain structure, or use the atlas along with the automatic mouse brain MRI segmentation tools, we ask you to kindly cite the following papers: Ma D, Cardoso MJ, Modat Automatic structural parcellation of mouse brain MRI using multi-atlas label fusion. PloS one. 2014 Jan 27;9(1):e86576. http://journals.plos.org/plosone/article?
…To face these challenges, large-scale samples are essential, but single laboratories cannot obtain sufficiently large datasets to reveal the brain mechanisms underlying ASD. In response, the Autism Brain Imaging Data Exchange (ABIDE) initiative has aggregated functional and structural brain imaging data collected from laboratories around the world to accelerate our understanding Each collection was created through the aggregation of datasets independently collected across more than 24 international brain imaging laboratories and are being made available to investigators throughout
BRATS 2013 is a brain tumor segmentation dataset consists of synthetic and real images, where each of them is further divided into high-grade gliomas (HG) and low-grade gliomas (LG).
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BRATS 2014 is a brain tumor segmentation dataset.
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The BraTS 2015 dataset is a dataset for brain tumor image segmentation. It consists of 220 high grade gliomas (HGG) and 54 low grade gliomas (LGG) MRIs.
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BRATS 2016 is a brain tumor segmentation dataset. It shares the same training set as BRATS 2015, which consists of 220 HHG and 54 LGG. Its testing dataset consists of 191 cases with unknown grades.
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…It contains 285 brain tumor MRI scans, with four MRI modalities as T1, T1ce, T2, and Flair for each scan. The dataset also provides full masks for brain tumors, with labels for ED, ET, NET/NCR.
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Prediction of Finger Flexion IV Brain-Computer Interface Data Competition The goal of this dataset is to predict the flexion of individual fingers from signals recorded from the surface of the brain (electrocorticography This data set contains brain signals from three subjects, as well as the time courses of the flexion of each of five fingers.
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…It measures brain development (via structural, task functional, and resting state functional imaging), social, emotional, and cognitive development, mental health, substance use and attitudes, gender identity
EPISURG is a clinical dataset of $T_1$-weighted magnetic resonance images (MRI) from 430 epileptic patients who underwent resective brain surgery at the National Hospital of Neurology and Neurosurgery Acknowledgements If you use this dataset for your research please cite the following publications: Pérez-García F., Rodionov R., Alim-Marvasti A., Sparks R., Duncan J.S., Ourselin S. (2020) Simulation of Brain
The Individual Brain Charting (IBC) project aims at providing a new generation of functional-brain atlases. variability—are publicly available as means to support the investigation of functional segregation and connectivity as well as individual variability with a view to establishing a better link between brain
IXI Dataset is a collection of 600 MR brain images from normal, healthy subjects.
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Click to add a brief description of the dataset (Markdown and LaTeX enabled).
…The enrolled participants are followed in an accelerated longitudinal design that involves structural and functional imaging of the brain along with extensive neuropsychological and clinical assessments
The NVALT-11 study considered the effect of profylactic brain radiation versus observation in ($m$=174) patients with advanced non-small cell lung cancer.
The fastMRI dataset includes two types of MRI scans: knee MRIs and the brain (neuro) MRIs, and containing training, validation, and masked test sets. Brain MRI: Data from 6,970 fully sampled brain MRIs obtained on 3 and 1.5 Tesla magnets. The raw dataset includes axial T1 weighted, T2 weighted and FLAIR images.
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