766 datasets found

The dataset used in this study for brain sMRI analysis, which includes seven public datasets, including one dataset for pre-training and other six datasets across three diseases...

Brain lesion segmentation provides a valuable tool for clinical diagnosis, and convolutional neural networks (CNNs) have achieved unprecedented success in the task. Data...

Abdominal aortic aneurysm screening and detection

A dataset of LGE scans with real scar tissue for evaluation of the ScarGAN approach

A dataset of LGE scans with simulated scar tissue to augment the training dataset of a segmentation network

The CRC-LNM dataset includes 52 CT images of 145 lymph nodes with confirmed metastasis through both pathology and imaging.

The ABD-LN dataset comprises 86 CT images from 86 patients, totaling 595 identified abdominal lymph nodes.

The LiTS17 and SLiver07 datasets are used for training and testing the proposed SAR-U-Net method.

The OCT2Confocal dataset is the first to include in-vivo grayscale OCT and corresponding ex-vivo colored confocal images.

COVID-19 pandemic has spread rapidly and caused a shortage of global medical resources. The efficiency of COVID-19 diagnosis has become highly significant.

The dataset used in the paper is fastMRI, SMS, and uMRI datasets. The fastMRI dataset is a large open-access MRI dataset. The SMS dataset is a dataset of T1WI and T2WI images....

Polyp segmentation dataset

The proposed architecture uses a CNN-based approach to detect COVID-19 from chest X-ray images. The dataset is used to train and evaluate the proposed model.

The prostate MRI dataset is a collection of diffusion-weighted MRI images of prostate cancer patients.

Magnetic resonance elastography (MRE) data for prostate segmentation

The multimodal brain tumor image segmentation benchmark (brats).

COVID-19 CT dataset for predicting COVID-19 from chest CT images using attentional convolutional network.

Chest X-ray images dataset for COVID-19 pneumonia detection

Chest X-ray images dataset used for COVID-19 severity classification

A small dataset of 65 panoramic images for automatic detection of atherosclerotic carotid plaques.