700 datasets found

The training dataset is a collection of the publicly available Arabic corpora listed below: The unshuffled OSCAR corpus (Ortiz Su´arez et al., 2020). The Arabic Wikipedia dump...

Diabetic retinopathy (DR) is a leading cause of vision loss in the world and numerous cutting-edge works have built powerful deep neural networks (DNNs) to automatically...

The dataset used in this paper is the SIIM-ACR Pneumothorax Segmentation Challenge dataset, which contains 12,047 training images and 3,205 testing images.

Low Dose Computed Tomography (LDCT) image denoising dataset

The Brain Tumor Segmentation (BraTS) 2019 dataset provides 335 training subjects, 125 validation subjects and 167 testing ones, each with four MRI modality sequences (T1, T1ce,...

Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography

This dataset is used for semantic segmentation of bitewing radiography images. The goal is to segment the images into caries, enamel, dentin, pulp, crowns, restoration and root...

The Lung Image Database Consortium (LIDC) dataset contains 1609 2D thoracic CT scans belonging to 214 subjects.

A dataset of real low-dose PET scans acquired using a United Imaging uExplorer scanner.

The Monkeypox Skin Images Dataset (MSID) is a dataset of images of monkeypox and other skin conditions.

The dataset used in this study is a publicly available dataset for monkeypox disease recognition, which includes images of monkeypox and similar skin conditions.

The MUSIC dataset used in this paper for spectral CT reconstruction.

The dataset used in this paper for spectral CT reconstruction using deep learning.

MRI images super-resolution reconstruction using deep learning techniques

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