219 datasets found

The dataset used for training and testing the proposed deep co-training method for semi-supervised image segmentation.

Medical image segmentation task using cardiac magnetic resonance images from different hospitals.

The dataset used for training and validation of the EigenRank algorithm for data subset selection and failure prediction in deep learning based medical image segmentation.

A large annotated medical image dataset for the development and evaluation of segmentation algorithms.

Medical image segmentation using the proposed AgileFormer model

Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: Is the problem solved?

A novel domain adaptation framework for medical image segmentation

Evaluation of algorithms for Multi-Modality Whole Heart Segmentation: An open-access grand challenge.

Two cardiac computed tomography (CT) datasets consisting of 760 volumes across the whole cardiac cycle from 39 patients, and of 60 volumes from 60 patients respectively were...

A dataset for multi-organ segmentation problem, filling the gap of extendable multi-domain learning in image segmentation.

The dataset used in the paper is a real-world dataset for testing the parametric efficiency of quadratic networks.

The dataset used for medical image segmentation.

The dataset used for medical image segmentation.

The dataset used for medical image segmentation.

The dataset used for polyp segmentation in endoscopic images, gland segmentation in histology images, breast cancer segmentation in ultrasound images, and fluid region...

The dataset used for vestibular schwannoma MRI segmentation

The dataset used in this paper is a collaborative filtering dataset, specifically the Million Song Dataset (MSD), which contains listening counts from 1 million users on 50,000...

The MSD Spleen dataset consists of n = 61 portal-venous phase contrast-enhanced abdominal CT scans, out of which n = 41 (67%) contained annotations for the spleen.

The MSD Liver dataset consists of n = 201 portal-venous phase contrast-enhanced abdominal CT scans, out of which n = 131 (65%) contained annotations for the liver and liver tumors.

The Medical Segmentation Decathlon (MSD) is a collection of 10 benchmark datasets for segmentation spanning different body parts and modalities.