SR-Reg is a brain MR-CT registration dataset, deriving from SynthRAD 2023 (https://synthrad2023.grand-challenge.org/). This dataset contains 180 subjects preprocessed images, and each subject comprises a brain MR image and a brain CT image with corresponding segmentation label.
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…Source-code and summaries are provided for a processing pipeline, brain activity group analysis, and estimating baseline classification performance.
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…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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Intracranial hemorrhage (ICH) is a pathological condition characterized by bleeding inside the skull or brain, which can be attributed to various factors. To address this, we develop the Brain Hemorrhage Segmentation Dataset (BHSD), which provides a 3D multi-class ICH dataset containing 192 volumes with pixel-level annotations and 2200 volumes with slice-level
…Available on 🤗 : JetBrains-Research/commit-chronicle
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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
Seizures and seizure-like rhythmic and periodic brain activity known as “ictal-interictal-injury continuum” (IIIC) patterns are frequently detected during brain monitoring with electroencephalography (
WebBrain-Raw is a large-scale dataset built from English Wikipedia articles and their crawlable Wikipedia references.
…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.
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.
…Each patient’s brain includes around 150 scans on average.
…Normal tissue from mouse and rat species; liver, brain, lung, heart, pancreas, spleen, kidney organs; Masson's Trichrome and H&I staining.
MRI-based artificial intelligence (AI) research on patients with brain gliomas has been rapidly increasing in popularity in recent years in part due to a growing number of publicly available MRI datasets Notable examples include The Cancer Genome Atlas Glioblastoma dataset (TCGA-GBM) consisting of 262 subjects and the International Brain Tumor Segmentation (BraTS) challenge dataset consisting of 542 subjects The UCSF-PDGM dataset includes 501 subjects with histopathologically-proven diffuse gliomas who were imaged with a standardized 3 Tesla preoperative brain tumor MRI protocol featuring predominantly 3D
…Imagen: Text-to-Image Diffusion Models: Imagen is a state-of-the-art text-to-image diffusion model developed by the Google Research Brain Team. A brain riding a rocketship heading towards the moon. A dragon fruit wearing a karate belt in the snow. A small cactus wearing a straw hat and neon sunglasses in the Sahara desert.
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This brain tumor dataset contains 3064 T1-weighted contrast-enhanced images with three kinds of brain tumor. Detailed information on the dataset can be found in the readme file.
V2X-Sim, short for vehicle-to-everything simulation, is the a synthetic collaborative perception dataset in autonomous driving developed by AI4CE Lab at NYU and MediaBrain Group at SJTU to facilitate collaborative
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…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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Learn2Reg covers a wide range of anatomies (brain, abdomen, and thorax), modalities (ultrasound, CT, MR), availability of annotations, as well as intra- and inter-patient registration evaluation.
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…The data consist of 283 high-resolution pictures (1600x1200 pixels) of mice brain slices acquired through a fluorescence microscope.
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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
EEEyeNet is a dataset and benchmark with the goal of advancing research in the intersection of brain activities and eye movements.
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…published at NeurIPS Datasets & Benchmarks '21) https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/file/bd686fd640be98efaae0091fa301e613-Paper-round2.pdf Motivation We are interested in building brain In our target future use case, a user would actively use a keyboard and mouse as usual, but also wear a non-intrusive headband sensor that would passively provide real-time measurements of brain activity fNIRS recordings Multivariate (D=8) time-series representing brain activity throughout the session, recorded by a sensor probe placed on the forehead and secured via headband All measurements are recorded Publications The Tufts fNIRS Mental Workload Dataset & Benchmark for Brain-Computer Interfaces that Generalize Zhe Huang, Liang Wang, Giles Blaney, Christopher Slaughter, Devon McKeon, Ziyu Zhou, Robert
VesselGraph is a dataset of whole-brain vessel graphs based on specific imaging protocols.
…The data is obtained via a simulation that contains all of the currently (2021) known and well modeled "messy biological details" that relate to the operation of single neurons in the brain.
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…It consists of two fully annotated volumes: one electron microscopy (EM) volume containing nearly the entire zebrafish brain with around 170,000 nuclei; and one micro-CT (uCT) volume containing part of
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…It is used for 3D axon instance segmentation of brain cortical regions.
The H01 dataset is a 1.4 petabyte rendering of a small sample of human brain tissue, released by a collaboration between the Lichtman Laboratory at Harvard University and Google. The dataset comprises imaging data that covers roughly one cubic millimeter of brain tissue, and includes tens of thousands of reconstructed neurons, millions of neuron fragments, 130 million annotated H01 is thus far the largest sample of brain tissue imaged and reconstructed in this level of detail, in any species, and the first large-scale study of synaptic connectivity in the human cortex that spans The primary goals of this project are to produce a novel resource for studying the human brain and to improve and scale the underlying connectomics technologies.
The Algonauts dataset provides human brain responses to a set of 1,102 3-s long video clips of everyday events. The brain responses are measured with functional magnetic resonance imaging (fMRI). fMRI is a widely used brain imaging technique with high spatial resolution that measures blood flow changes associated Splits: Training: The training set consists of 1,000 video clips and the associated brain responses. In the second track, brain responses provided are from selected voxels across the whole brain showing reliable responses to videos. Test: The test set consists of 102 short videos. The associated brain responses will be released at a later date. For further details see here.
…The data is part of the Allen Brain Observatory Neuropixels dataset (©2019 Allen Institute for Brain Science, available from https://portal.brain-map.org/explore/circuits/visual-coding-neuropixels). The original LFP data used for this analysis is available as part of the Allen Brain Observatory AWS Public Data Set https://registry.opendata.aws/allen-brain-observatory/.
…Partnering with Princeton University, the team at Google Brain aims to grow the community around machine learning for mechanical ventilation control.
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Ultra-high field MRI enables sub-millimetre resolution imaging of human brain, allowing to disentangle complex functional circuits across different cortical depths. Segmentation, meant as the partition of MR brain images in multiple anatomical classes, is an essential step in many functional and structural neuroimaging studies. In this work, we design and test CEREBRUM-7T, an optimised end-to-end CNN architecture, that allows to segment a whole 7T T1w MRI brain volume at once, without the need of partitioning it into 2D or 3D
CheXphoto is a competition for x-ray interpretation based on a new dataset of naturally and synthetically perturbed chest x-rays hosted by Stanford and VinBrain. With the launch of the CheXphoto competition, we are pleased to announce the release of an additional set of x-ray film images provided by VinBrain, a subsidiary of Vingroup.
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3D confocal stacks with corresponding 2D Light-field microscope images
This brain anatomy segmentation dataset has 1300 2D US scans for training and 329 for testing.
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Electrophysiological data from implanted electrodes in the human brain are rare, and therefore scientific access to it has remained somewhat exclusive. In every case, electrode positions have been carefully registered to brain anatomy.
LibriTTS is a multi-speaker English corpus of approximately 585 hours of read English speech at 24kHz sampling rate, prepared by Heiga Zen with the assistance of Google Speech and Google Brain team members
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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.
The Brain-Score platform aims to yield strong computational models of the ventral stream. We enable researchers to quickly get a sense of how their model scores against standardized brain benchmarks on multiple dimensions and facilitate comparisons to other state-of-the-art models. At the same time, new brain data can quickly be tested against a wide range of models to determine how well existing models explain the data. Brain-Score is organized by the Brain-Score team in collaboration with researchers and labs worldwide. This quantified approach lets us keep track of how close our models are to the brain on a range of experiments (data) using different evaluation techniques (metrics).
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The goal of the "BCI Competition" is to validate signal processing and classification methods for Brain-Computer Interfaces (BCIs).
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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.
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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