60 datasets found

Clinical brain CT scans dataset used for anomaly detection in brain CT scans

The dataset used in the paper for whole heart segmentation.

The dataset used in this paper for multi-label deep regression and unordered pooling for holistic interstitial lung disease pattern detection.

The Lung Tissue Research Consortium (LTRC) dataset provides complete ILD labeling at the per-voxel or per-pixel level.

Chest X-ray datasets used to train machine learning models, potentially suffering from population, prevalence, and annotation shift biases.

The dataset used for training and testing the Conditional Generative Adversarial Networks (cGAN) for estimating tissue oxygen saturation from RGB images.

A dataset of pathological OCT scans for photoreceptor layer segmentation

A curated dataset of CT scan images of COVID-19 from India, used for training and testing machine learning models.

Abdominal organ segmentation from medical imaging is a topic that has been researched for several years. The dataset was acquired by Siemens dual-source 64-slice CT scanner and...

A real COVID-19 dataset containing 666 3D chest CT scans acquired from 242 patients who are confirmed with COVID-19.

Italian dataset of COVID-19 chest CT scans.

COVID-19 is a world-wide disease that has been declared as a pandemic by the World Health Organization. Computer Tomography (CT) imaging of the chest seems to be a valid...

A database of 332 PA chest X-ray images for research purposes.

A database of 7517 PA chest X-ray images for research purposes.

A hospital-scale chest X-ray database, namely “ChestX-ray8”, which comprises 108,948 frontal-view X-ray images of 32,717 unique patients with the text-mined eight common disease...

The dataset used in the paper to evaluate the proposed two-stage approximately orthogonal training framework (TAOTF) for Deep Neural Networks (DNNs).

The dataset used in the paper to evaluate the proposed two-stage approximately orthogonal training framework (TAOTF) for Deep Neural Networks (DNNs).

The dataset used in the paper is a Shepp-Logan phantom, a high-resolution image of size 2563 and a low-resolution image of 1283 voxels.

The dataset is used for training and testing the proposed VTGAN model for fundus-to-angiogram synthesis and disease prediction.

COVID-CT dataset that has been used in this study is publicly available. There are 349 images of COVID-19 collected from 216 patients. The non-COVID-19 data contains 397 samples.