225 datasets found

The Prostate dataset is a diverse collection of T2-weighted MRI prostate images and corresponding masks, spanning six distinct domains.

Multi-parametric MRI scans from 2000 patients were used for BraTS2021, 1251 of which were provided with segmentation labels to the participants for developing their algorithms,...

A dataset of real animal X-ray images and phantom X-ray images for catheter and guidewire segmentation.

A shape-sensitive loss function for catheter and guidewire segmentation using a vision transformer network.

Medical image segmentation dataset

Medical image segmentation dataset

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

Polyp Segmentation in Endoscopic Images dataset, RETOUCH dataset

Nuclei Segmentation dataset for medical image segmentation.

Lung Segmentation dataset for medical image segmentation.

Fast and accurate reconstruction of magnetic resonance (MR) images from under-sampled data is important in many clinical applications. In recent years, deep learning-based...

Medical image segmentation dataset with multiple annotations and uncertainty quantification

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used CIFAR-10, CIFAR-100, ImageNet, CUB-200-2011, and Stanford Dogs datasets.

Four image datasets for medical image segmentation: thyroid nodule, liver and kidney, breast lesion, and skin lesion.

The proposed 2D-3D FCN ensemble is constructed in two phases as shown in Fig. 1. In Phase I, the 2D FCN and 3D FCN architectures are adapted to the specific dataset using a...

The dataset used for training and testing the Slide-SAM model, which consists of 3D medical images and their corresponding segmentation masks.

The dataset used for training and testing the Slide-SAM model, which consists of 3D medical images and their corresponding segmentation masks.

The dataset used for training and testing the Slide-SAM model, which consists of 3D medical images and their corresponding segmentation masks.

nnu-net: Self-adapting framework for u-net-based medical image segmentation.

Segmentation of retinal OCT B-scans into 7 retinal layers and accumulated fluid.