154 datasets found

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

The Brain Tumor Segmentation (BraTS) Challenge 2021 dataset, which provides a valuable resource for addressing challenges specific to resource-limited settings, particularly the...

A benchmark dataset and evaluation methodology for video object segmentation.

The MSD Spleen dataset consists of n = 61 portal-venous phase contrast-enhanced abdominal CT scans, out of which n = 41 (67%) contained annotations for the spleen.

The MSD Liver dataset consists of n = 201 portal-venous phase contrast-enhanced abdominal CT scans, out of which n = 131 (65%) contained annotations for the liver and liver tumors.

The Medical Segmentation Decathlon (MSD) is a collection of 10 benchmark datasets for segmentation spanning different body parts and modalities.

A multi-level ConvLSTM model for the automatic segmentation of left ventricle myocardium in infarcted porcine cine MR images

The SMU-Net dataset is not explicitly mentioned in the paper, but it is used as a benchmark for the proposed method.

The PH2 dataset used for evaluation of the proposed deep learning model for automatic skin lesion segmentation on dermoscopic images.

Geometry Sharing Network (GS-Net) for 3D point cloud classification and segmentation

The BraTS 2020 challenge dataset is a multimodal MRI brain tumor segmentation dataset. It contains 369 subjects with 4 MRI modalities (T2 weighted FLAIR, T1 weighted, T1...

Automatic segmentation of brain tumors is an essential but challenging step for extracting quantitative imaging biomarkers for accurate tumor detection, diagnosis, prognosis,...