15 datasets found

Dataset for abdominal organ segmentation

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.

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

Retinal fundus images have been extensively used for clinical analysis of various ocular diseases, but the quality of fundus images is critical to the diagnosis and screening of...

LesionPaste is a one-shot anomaly detection framework for medical images that utilizes true anomalies from a single sample and synthesizes artificial anomalous samples.

Medical images, captions, and textual references

Kvasir-SEG: an open-access dataset of gastrointestinal polyp images and corresponding segmentation masks, manually annotated by a medical doctor and then verified by an...

The abdominal CT scans used for the Medical Out-of-Distribution (MOOD) challenge

The HCP30 dataset used for the Medical Out-of-Distribution (MOOD) challenge

The dataset used for the Medical Out-of-Distribution (MOOD) challenge

Anomaly detection is the process of identifying atypical data samples that significantly deviate from the majority of the dataset. In the realm of clinical screening and...