60 datasets found

Low dose computed tomography dataset used for training and testing the proposed TED-net model

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...

A dataset of chest X-rays from Montgomery and Shenzen hospitals, containing 336 normal cases and 326 tuberculosis cases.

A large DNN, containing 3 stacked modules. The segmentation module is an U-Net, trained beforehand to receive X-rays and output segmentation masks.

The Medical Segmentation Decathlon dataset is a benchmark for medical image segmentation, containing 131 CT volumes.

The dataset used for the segmentation of the Planning Target Volume (PTV) in Total Marrow and Lymph Node Irradiation (TMLI) treatment.

The dataset used in this paper is a CT slice dataset, which comprises a collection of 53,500 CT images obtained from 74 different patients, encompassing 43 males and 31 females.

LUNA16 dataset is a subset of the largest public dataset for pulmonary nodules, the LIDC-IDRI dataset.

A dataset for vertebrae detection and localization in CT scans

CheXNet dataset

CoronaHack Chest X-Ray Dataset

The dataset consists of T1-weighted brain MRI images of patients, with manual segmentation of anatomical structures provided.

The MMAC dataset is an extensive collection of color fundus images dedicated to research on myopic maculopathy.

A separate dataset of 3D chest CT volumes and radiology reports, used for external evaluation of the proposed BIUD model.

A large dataset of 3D chest CT volumes and corresponding radiology reports, used for training and testing the proposed BIUD model.

In silico bone US simulation framework that synthesizes realistic US images from diagnostic CT volume.

The Total Segmentator dataset contains 1204 CT images with labels of 104 anatomical structures.

The NIH-Lymph Node (NIH-LN) dataset includes 176 chest-abdomen-pelvis CT scans.

Kaggle US simulation & segmentation dataset is a dataset of ultrasound images, annotated with eight anatomical structures.

AbdomenCT-1K dataset is a large-scale dataset of abdominal CT scans, annotated with four anatomical structures: liver, kidney, spleen, and pancreas.