-
Stanford Fullysampled 3D FSE Knees
The Stanford Fullysampled 3D FSE Knees dataset is a public MRI dataset of 20 fully-sampled k-space volumes of knees. -
Stanford 2D FSE
The Stanford 2D FSE dataset is a public dataset of 89 fully-sampled MRI volumes of various anatomies. -
Pre-processed Connectomes Project
The pre-processed connectomes project repository of manually corrected skull-stripped T1-weighted anatomical MRI data. -
Neurofeedback Skull-stripped (NFBS) repository dataset
Skull Stripping involves separating brain tissue, including grey matter and white matter, from non-brain voxels such as the skull, scalp, and dura mater. -
BraTS 2021 dataset
The Brain Tumor Segmentation (BraTS) Challenge 2021 dataset, which provides a valuable resource for addressing challenges specific to resource-limited settings, particularly the... -
In-vivo fully sampled T2-weighted k-space data
In-vivo fully sampled T2-weighted k-space data from MR scanner -
Fully sampled multi-coil k-space data
Fully sampled multi-coil k-space data from the scanner, retrospectively under-sampled to optimize the under-sampling pattern of in-vivo k-space data -
Multi-shell Human Dataset
A dataset for testing the proposed method for sparse spherical deconvolution. -
Tractometer Benchmark
A dataset for testing the proposed method for sparse spherical deconvolution. -
Simulated Motion Dataset for MRI
The dataset used in this paper is a simulated motion dataset for MRI scans, created to test the proposed motion correction method. -
OASIS dataset
The dataset consists of T1-weighted brain MRI images of adults, with manual segmentation of anatomical structures provided. -
BrainWeb database
The BrainWeb database is a collection of MRI images with known noise levels. -
IXI dataset
The dataset consists of T1-weighted brain MRI images of patients, with manual segmentation of anatomical structures provided. -
On the Rician distribution of noisy MRI data
The Rician distribution of noisy MRI data. -
Cervical Cancer Segmentation on Multiparametric MRI
A dataset of multiparametric MRI images of cervical cancer patients for segmentation and analysis.
