165 datasets found

A dataset comprising 10 out-of-phase 3pt Dixon MRI volumes was used for algorithm development and testing.

3D X-ray microscope data for 3D object detection, segmentation, and metrology for buried structures in advanced IC packages

Medicalsemi-supervisedsegmentationisatechniquewhereamodelistrainedtosegmentobjectsofinterestinmedicalimageswithlimitedannotateddata.

The Spot-the-difference self-supervised pre-training for anomaly detection and segmentation dataset.

The MOTS20 dataset is used for multi-object tracking and segmentation.

The dataset used in this paper for segmentation of arterial walls in intravascular ultrasound cross-sectional images.

The dataset used for the experiments in the paper, which includes ImageNet, MS COCO, Cityscapes, and ADE20K datasets.

Automated medical image segmentation can assist doctors to diagnose faster and more accurate. Deep learning based models for medical image segmentation have made great progress...

The Multimodal Brain Tumor Segmentation Challenge 2020 dataset was used as our primary dataset for brain tumor classification and segmentation.

The Brain Tumor Segmentation (BraTS) Challenge Africa (BraTS-Africa) dataset, which provides a valuable resource for addressing challenges specific to resource-limited settings,...

We develop techniques for refining representations for fine-grained classification and segmentation tasks in a self-supervised manner.

The Myocardial pathology segmentation (MyoPS) dataset is a multi-sequence CMR dataset that contains in total 25 volumes and 102 slices in the training set.

The SCGM challenge data set is composed of magnetic resonance imaging (MRI) data of different subjects.

The BraTS-2017 and ISLES-2015 segmentation benchmarks

The dataset used for self-supervised learning of 3D medical images.

The dataset for low-dose CT image enhancement and segmentation.

Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: Is the problem solved?

SAMRS: Scaling-up remote sensing segmentation dataset with segment anything model

A hyperspectral image dataset with 4 classes, captured over the Kennedy Space Center, FL, by the NASA AVIRIS instrument.

The dataset used for vestibular schwannoma MRI segmentation