766 datasets found

MRI images super-resolution reconstruction using deep learning techniques

The CPC-Paired Dataset is a dataset used for colorectal polyp classification, consisting of paired white-light (WL) and narrow-band imaging (NBI) images.

A dataset of low-dose CT images used for training and testing low-dose CT reconstruction algorithms

Blind CT image quality assessment using DDPM-derived content and transformer-based evaluator

The dataset used in the paper is a set of dual-energy CT sinograms and reconstructed images.

The dataset of Chest X-Ray Images Pneumonia

The dataset used in this paper is not explicitly described. However, it is mentioned that the authors used a dataset for medical image classification, specifically for diabetic...

The DeepLesion dataset is a large-scale dataset containing measurements and 2D bounding-boxes of over 32K lesions from a variety of body parts on computed tomography (CT) images.

Abdominal MRI dataset used for motion correction

The dataset used in this paper is a small dataset of Common Imaging Signs of Lung diseases (CISLs) with 696 samples.

The LISS database of Common Imaging Signs of Lung diseases (CISLs) contains 9 types of CISLs, including Ground Glass Opacity (GGO), lobulation, calcification, Cavity &...

The CHASE_DB1 dataset is a publicly available dataset for retinal vessel segmentation.

The dataset used in the paper is HAM10000, which is a dermoscopic image classification dataset. It contains 10,015 dermoscopic images categorized into 7 lesion types.

HARP dataset used for validation

CC-359 dataset used for validation

Hippocampus segmentation dataset used in the paper

MRI dataset consisting of 302 unlabeled volumes and CT dataset consisting of 613 unlabeled and 20 labeled volumes.

Cardiac Atlas database containing short-axis cine MRI images of 100 patients with coronary artery disease and prior myocardial infarction.

Chest X-ray dataset for abnormality localization in heterogeneous data with cross-domain self-supervised learning

Chest X-ray dataset for abnormality localization in heterogeneous data with cross-domain self-supervised learning