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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…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
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…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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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
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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…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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…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.
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?
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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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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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.
Click to add a brief description of the dataset (Markdown and LaTeX enabled).
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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
…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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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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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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