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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2-PM Vessel is an open-source volumetric brain vasculature dataset obtained with two-photon microscopy at Focused Ultrasound Lab, at Sunnybrook Research Institute (affiliated with University of Toronto The dataset contains a total of 12 volumetric stacks consisting of images of mouse brain vasculature and tumour vasculature.
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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
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…study subjects with AD, as well as those who may develop AD and controls with no signs of cognitive impairment.2 Researchers at 63 sites in the US and Canada track the progression of AD in the human brain
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The Algonauts 2023 Challenge focuses on predicting responses in the human brain as participants perceive complex natural visual scenes. Through collaboration with the Natural Scenes Dataset (NSD) team, the Challenge runs on the largest suitable brain dataset available, opening new venues for data-hungry modeling.
The BBBP dataset comes from a study focused on modeling and predicting the permeability of the blood-brain barrier. The BBBP dataset contains binary labels indicating whether a compound can penetrate the blood-brain barrier (BBB) or not.
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…The EEG amplifier used in the experiment was a BrainAmp (Brain Products; Munich, Germany). The channels were nasion-referenced and grounded to electrode AFz.
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…Experimental runs began and ended with a blank screen (duration 4 s) References 1 Scherer R, Faller J, Friedrich EVC, Opisso E, Costa U, Kübler A, et al. (2015) Individually Adapted Imagery Improves Brain-Computer
…pre-operative baseline multi-parametric magnetic resonance imaging (mpMRI) scans, and focuses on the evaluation of state-of-the-art methods for (Task 1) the segmentation of intrinsically heterogeneous brain
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Click to add a brief description of the dataset (Markdown and LaTeX enabled).
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Multimodal Brain Tumor Segmentation Challenge 2018
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Multimodal Brain Tumor Segmentation Challenge 2019
This dataset is a combination of the following three datasets : figshare, SARTAJ dataset and Br35H This dataset contains 7022 images of human brain MRI images which are classified into 4 classes: glioma
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Non-contrast head/brain CT of patients with head trauma or stroke symptoms.
…The challenge is carried out on three large and diverse datasets from adult Drosophila melanogaster brain tissue, comprising neuron segmentation ground truth and annotations for synaptic connections. Description We provide three datasets, each consisting of two (5 μm)3 volumes (training and testing, each 1250 px × 1250 px × 125 px) of serial section EM of the adult fly brain.
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…launched in October 2010, with substantial initial funding from the Biotechnology and Biological Sciences Research Council (BBSRC), followed by support from the Medical Research Council (MRC) Cognition & Brain Sciences Unit (CBU) and the European Union Horizon 2020 LifeBrain project.
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
…Each file is a recording of brain activity for 23.6 seconds. The corresponding time-series is sampled into 4097 data points. Specifically y in {1, 2, 3, 4, 5}: 5 - eyes open, means when they were recording the EEG signal of the brain the patient had their eyes open 4 - eyes closed, means when they were recording the EEG signal the patient had their eyes closed 3 - Yes they identify where the region of the tumor was in the brain and recording the EEG activity from the healthy brain area 2 - They recorder the EEG from the area
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…Images are divided into 6 classes: four of the most widely used fetal anatomical planes (Abdomen, Brain, Femur and Thorax), the mother’s cervix (widely used for prematurity screening) and a general category Fetal brain images are further categorized into the 3 most common fetal brain planes (Trans-thalamic, Trans-cerebellum, Trans-ventricular) to judge fine grain categorization performance.
…consists of 12,000 real fluorescence microscopy images obtained with commercial confocal, two-photon, and wide-field microscopes and representative biological samples such as cells, zebrafish, and mouse brain
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brain-image-text trimodal datasets
…Human brain mapping 38.11 (2017): 5391-5420.
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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…diagnose intracranial aneurysms and to extract the neck for a clipping operation in medicine and other areas of deep learning, such as normal estimation and surface reconstruction. 103 3D models of entire brain
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…EEG data was recorded by a multichannel BrainAmp EEG amplifier with thirty active electrodes (Brain Products GmbH, Gilching, Germany) with linked mastoids reference at 1000 Hz sampling rate.
Dataset from the article A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface [1]_. References [1] Zhou B, Wu X, Lv Z, Zhang L, Guo X (2016) A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface.
…Four BrainAmp amplifiers were used for this purpose, using a temporal analog high-pass filter with a time constant of 10 s. The data were re-referenced to common average reference offline. "Beamforming in noninvasive brain–computer interfaces." IEEE Transactions on Biomedical Engineering 56.4 (2009): 1209-1219.
…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.
Data was acquired to investigate the effects of morphine withdrawal in rats, both in the brain neurochemistry and ultrasonic vocalisation. Each rat was immediately decapitated after USVs recording session, and its brain tissues were frozen. The USVs were recorded individually for each rat, in a dark room with dim red light. For each rat, tissue samples of 6 brain structures were extracted: medial prefrontal cortex (mPFC), nucleus accumbens (NAcc), striatum (Cpu), hippocampus (Hipp), amygdala and ventral tegmental area (VTA
The Open Access Series of Imaging Studies (OASIS) is a project aimed at making neuroimaging data sets of the brain freely available to the scientific community.
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