144 datasets found

Fast and accurate reconstruction of magnetic resonance (MR) images from under-sampled data is important in many clinical applications. In recent years, deep learning-based...

The dataset is a collection of 3D multi-modality MRI spine images for intervertebral disc localization and segmentation.

Vestibular schwannoma growth prediction from longitudinal MRI by time-conditioned neural fields

A dataset of multiparametric MRI images of cervical cancer patients for segmentation and analysis.

The cardiac dataset is a dataset of MRI images acquired from 100 subjects, with 10 images per subject, using 32 channels and 3T MRI scanner.

Two publicly available datasets with histological sections and an ex vivo 3D MRI of the same subject. A 3D similarity transform between the stack of histological sections and...

The ASPIRE Registry dataset contains data from patients who underwent MRI and RHC within 48 hours.

The TCGA_LGG database is a repository of brain images for the study of lower grade gliomas.

The Harvard Whole Brain Atlas dataset contains MRI and PET images of patients with various brain conditions.

Multimodal Brain Tumor Image Segmentation Challenge (BraTS) 2018 dataset used for brain tumor segmentation and overall survival prediction.

The sulcal and gyral curve extraction method (TRACE) dataset contains cortical sulcal curves extracted from T1-weighted MRI of 444 subjects.

The dataset used in the paper is a subset of the Human Connectome Project dataset, containing functional connectivity MRI scans from 865 subjects.

Simultaneous single-and multi-contrast super-resolution for brain MRI images

Multi-contrast super-resolution MRI through a progressive network

Multi-contrast MRI super-resolution

A multi-site ovarian tumor MRI dataset for evaluating the performance of medical image segmentation models.

The fastmri dataset is used for MRI reconstruction. It contains fully sampled knee MR images and k-spaces from 1500 patients obtained from 1.5 and 3.0T scanners.

The BraTS21 dataset consists of 1251 brain MRI scans of four different weightings (T1, T1-CE, T2, FLAIR).

The ATLAS dataset is used for stroke MRI generation. The dataset contains 220 T1w images, which have diverse stroke lesions.

The BRATS 2018 dataset is used for brain tumor MRI generation. 210 subjects in the training dataset labeled as ’HGG3.’