26 datasets found

A multi-view multi-stage and multi-window framework for pulmonary artery segmentation from CT scans

This study employs a diverse range of post-processed, multi-annotated medical image segmentation datasets, which exhibit significant variations in the ground truth, to train and...

The QUBIQ dataset is a multi-rater, multi-center, multi-modality dataset that includes both 2D and 3D segmentation tasks. It features various modalities such as MRI and CT;...

The REFUGE dataset is regarded as the source domain and RIM-ONE-r3 and Drishti-GS datasets are treated as target domains.

The GlaS dataset contains 165 H&E-stained histopathology patches extracted from 16 WSIs.

The 2018 Data Science Bowl challenge dataset is used for nuclei cell image segmentation.

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

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 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.

The V-Net is a deep learning model for medical image segmentation that uses a U-Net architecture.

The 3D Unet is a deep learning model for medical image segmentation that uses a U-Net architecture.

The R2U-Net is a deep learning model for medical image segmentation that combines U-Net, ResNet, and recurrent neural network (RCNN).

Optic disc and cup segmentation dataset used for evaluating the efficiency of the proposed Translation Variant Convolution (TVConv) operator.

The nnu-net dataset

Automated segmentation of ultrasound images can assist medical experts with diagnostic and therapeutic procedures. Although using the common modality of ultrasound, one...

The dataset is used for training and testing the proposed model.

The dataset is used for evaluating the performance of the proposed model.