766 datasets found

Lesion detection in digital breast tomosynthesis (DBT) is an important and a challenging problem characterized by a low prevalence of images containing tumors.

Pulmonary lobes segmentation dataset used for training and validation of the proposed method

Pulmonary lobes segmentation dataset used for training and validation of the proposed method

The dataset is provided by PARSE 2022 Grand Challenge. The dataset contains 200 3D volumes provided in compressed NIFTI (.nii.gz) format and with refined pulmonary labels.

The 0.36T MRI dataset was acquired at the University College Hospital, Ibadan, Nigeria.

The dataset used in the paper is a chest CT scans dataset, which consists of 100 patients.

The dataset used in the paper is a multiphase cardiac CT scans dataset, which consists of 50 mitral valve prolapse patients and 50 coronary artery disease patients.

Brain tumor segmentation is a critical task for patient’s disease management. In order to automate and standardize this task, we trained multiple U-net like neural networks,...

Modern biomedical image analysis using deep learning often encounters the challenge of limited annotated data. To overcome this issue, deep generative models can be employed to...

COVIDx dataset, which is an ongoing project, i.e., the number of available examples may change over time. The snapshot of COVIDx used in this paper consists of 8851 CXR images...

The SMU-Net dataset is not explicitly mentioned in the paper, but it is used as a benchmark for the proposed method.

The dataset used for training and testing deep neural networks-based denoising models for CT imaging.

The dataset used in this paper is a collection of 51 seed images of lung nodules, which are used to train an autoencoder-based system to generate synthetic 3D lung nodule images.

The dataset used in this paper is a collection of 51 seed images of lung nodules, which are used to train an autoencoder-based system to generate synthetic 3D lung nodule images.

The proposed network is implemented in PyTorch using a single Tesla V100-DGXS-32GB GPU of an NVIDIA DGX station. For the ResNet-50 part, PyTorch default ImageNet pretrained...

CAMELYON-17 consists of 145 positive slides and 353 negative slides, where positive patches occupying less than 10% of the tissue area in positive slides.

Unsupervised anomaly detection dataset for multi-image visual question answering

The EyePACS dataset is a collection of retinal fundus images of individuals potentially suffering from diabetic retinopathy (DR), an eye disease associated with diabetes that is...

Liver lesion dataset for classification using synthetic data augmentation

The dataset used in the paper for posterior estimation of dynamic PET imaging using Conditional Variational Inference