21 datasets found

The NIH pancreas segmentation dataset contains 82 abdominal CT volumes. The width and height of each volume are 512, while the axial view slice number can vary from 181 to 466....

A new Multiorgan Lesion Segmentation (MLS) dataset that contains images of various organs, including brain, liver, and lung, across different imaging modalities—MR and CT.

The DRIVE dataset contains the curvilinear-shaped vessel. This dataset consists of 40 565 × 584 color retinal images, which are split into 20 training images and 20 test images.

The head CT scans dataset is used for training and evaluation of the proposed method.

The CQ500 dataset is a head CT scans dataset used for training and evaluation of the proposed method.

ExplainFix adopts two design principles: the “fixed filters” principle that all spatial filter weights of convolutional neural networks can be fixed at initialization and never...

The evaluation of prostate segmentation algorithms for mri challenge dataset

The computer-aided detection and diagnosis for prostate cancer based on mono and multi-parametric mri dataset

The NCI-ISBI 2013 challenge dataset

The dataset used for prostate cross-site segmentation

The dataset used in the paper is a set of sequential vision-and-language tasks, where each task consists of an image and a text input.

Automatic segmentation of retinal vessels in fundus images plays an important role in the diagnosis of some diseases such as diabetes and hypertension.

The HRF dataset contains 45 images, which is divided into 15/15/15 images for healthy patients, patients with diabetic retinopathy and glaucomatous patients.

Two benchmark datasets for blood vessel segmentation in retinal images

The dataset in this paper comes from the database of the Ultrasound Imaging Department of Peking University Shenzhen Hospital.

The CTFilm20K dataset is a large-scale head CT film database containing approximately 20,000 pictures, with various real-world warping scenarios and different contents.

A dataset for computer vision for medical infant motion analysis: state of the art and RGB-D data set.

The CHASE_DB1 dataset is a publicly available dataset for retinal vessel segmentation.

The proposed SA-UNet is evaluated on two publicly available retinal fundus image datasets: DRIVE and CHASE_DB1.

The CAMUS dataset includes 450 annotated patient sub-datasets consisting of TTE apical four- and two-chamber views.