91 datasets found

Three datasets for phase recognition, pupil segmentation, and lens segmentation that are publicly released to support reproducibility and allow further investigations for lens...

The ORIGA dataset contains 650 fundus images with 168 glaucomatous eyes and 482 normal eyes.

The MMWHS dataset, a dataset for multi-modality whole heart segmentation.

Dataset for abdominal organ segmentation

The AASCE dataset, which contains spinal anterior-posterior X-ray images of 352 subjects.

The Cephalometric X-ray dataset, which contains 6,504 cephalometric X-ray images of 4,280 subjects without overlapping patients in each set.

The REFUGE-2 dataset is an active challenge on classification of clinical Glaucoma.

The proposed framework is composed of two networks (see Fig 1). The encoder network q with parameters of φ computes qφ(z|x) : xi → zi. The encoder maps an input image xi ∈ X to...

BloodMNIST is a medical imaging dataset containing 9,000 images of blood samples, each with a size of 224x224x3.

PathMNIST is a medical imaging dataset containing 9,000 images of breast cancer tissue, each with a size of 224x224x3.

The MedMNIST dataset is a large standardized biomedical image collection, including 12 number of 2D datasets and 6 number of 3D datasets.

Semantic object segmentation is a fundamental task in medical image analysis and has been widely used in automatic delineation of regions of interest in 3D medical images, such...

A large annotated medical image dataset for the development and evaluation of segmentation algorithms.

The VFSS2022 dataset is a collection of 440 CT frames from Videofluoroscopic Swallowing Studies (VFSS) for instance segmentation in medical CT videos.

The NIH pancreas segmentation dataset contains 82 abdominal CT volumes. The width and height of each volume are 512, while the axial view slice number can vary from 181 to 466....

Fast MRI aims to reconstruct a high fidelity image from partially observed measurements. Exuberant development in fast MRI using deep learning has been witnessed recently....

Liver vessel segmentation based on 3D swin-transformer with inductive biased multi-head self-attention

The proposed network is implemented in PyTorch using a single Tesla V100-DGXS-32GB GPU of an NVIDIA DGX station. For the ResNet-50 part, PyTorch default ImageNet pretrained...

A new Multiorgan Lesion Segmentation (MLS) dataset that contains images of various organs, including brain, liver, and lung, across different imaging modalities—MR and CT.

MosMed is a publicly-available medical image dataset for COVID-19 detection.