47 datasets found

The BraTS 2018 training dataset included 285 cases (210 HGG and 75 LGG), each with four 3D MRI modalities (T1, T1c, T2 and FLAIR) rigidly aligned, resampled to 1x1x1 mm...

MRI thigh muscle segmentation dataset

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

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

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

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.

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

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.

Knee OsteoArthritis (KOA) dataset used for early detection of KOA (KL-0 vs KL-2) using Vision Transformer (ViT) model with selective shuffled position embedding and key-patch...

A large DNN, containing 3 stacked modules. The segmentation module is an U-Net, trained beforehand to receive X-rays and output segmentation masks.

Multi-modality MRI dataset for brain tumor segmentation

DR-Private is a private dataset of chest X-ray images with annotations.

ChestX-Det is a subset of NIH ChestX-14 with box annotations of 13 categories of diseases.

Brain tumor segmentation dataset

Brain tumor segmentation dataset

Brain tumor segmentation dataset