116 datasets found

A dataset used for medical image segmentation tasks

The Medical Segmentation Decathlon (MSD) dataset contains 282 CT scans in portal venous phase, all of which are pathological cases with pancreas and tumor annotation.

The BraTS21 dataset consists of 1251 brain MRI scans of four different weightings (T1, T1-CE, T2, FLAIR).

Medical image segmentation dataset used for pre-training and fine-tuning the SwinFUSE model.

The dataset used in the paper is not explicitly described, but it is mentioned that it is a large-scale medical image segmentation dataset.

A dataset of 50 transversal T2-weighted MR images of the prostate and corresponding segmentation ground truths

The dataset used for training and testing the proposed D-Persona model for multi-rater medical image segmentation.

Polyp(CVC-ClinicDB and ETIS-LaribPolypDB), Skin(ISIC-2018 Skin lesion segmentation challenge dataset)

The dataset used in the paper for medical image segmentation tasks.

The dataset used in the paper for medical image segmentation tasks.

The MoNuSeg dataset comprises 30 microscopic images from seven organs in the training set, with annotations of 21,623 individual nuclei, and 14 similar images in the test set.

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

Decathlon Prostate dataset is a public dataset for semi-supervised medical image segmentation.

MS-CMRSEG 2019 dataset is a public dataset for semi-supervised medical image segmentation.

ACDC dataset contains 100 samples with the cavity of the right ventricle (RV), the myocardium of the left ventricle (MYO), and the cavity of the left ventricle (LV) to be...

Semi-supervised medical image segmentation aims to leverage limited annotated data and rich unlabeled data to perform accurate segmentation.