154 datasets found

Endoscopic Submucosal Dissection (ESD) dataset, comprising 3 surgical videos with 300 frames, specifically from ESD surgery. The instrument and organ segmentation masks are...

The LERF-Mask dataset is a dataset for open-vocabulary 3D segmentation, where the goal is to segment anything in a 3D scene. The dataset is constructed by annotating three...

The dataset used in the paper is ScanNetV2, a real-world dataset for indoor scenes. It contains 1205 training scenes and 312 testing scenes, with instance-level object bounding...

The IRISA Team dataset is used for Task 2: Segment Map Content Area.

The REFUGE2 dataset is a multi-annotated dataset for optic-cup segmentation. The dataset consists of 1200 fundus images, each annotated by seven radiologists.

The BraTS2020 dataset is a widely-used benchmark for brain tumor segmentation. It contains 369 glioma patient samples with two glioma grades (LGG and HGG).

The TCIA-Glioma dataset is a multi-modal MRI scans dataset for brain tumor segmentation.

The rsna-asnr-miccai brats 2021 benchmark dataset is a multi-modal MRI scans dataset for brain tumor segmentation.

Anomaly detection is the process of identifying atypical data samples that significantly deviate from the majority of the dataset. In the realm of clinical screening and...

The dataset used in this paper is the MindBoggle dataset, which contains the cortical mesh data of 101 subjects aggregated from multiple sites.

The HFH dataset includes 50 T1-weighted MRI brain images from two different MRI vendors, with varying resolutions and contrasts. The image dimensions are 256×124×256 and...

The LPBA40 dataset contains 3D brain MRI scans of 40 healthy adults, with image dimensions of 256×124×256 and a voxel size of 0.8938×1.500×0.8594 mm³. Each scan is precisely...

The EADC-ADNI dataset contains MR images of 135 patients, with an image resolution of 197×233×189 and a voxel size of 1×1×1 mm³. The hippocampus annotations for each image were...

The BraTS2021 dataset is an important resource in the field of brain tumor segmentation, consisting of multi-modal magnetic resonance imaging (MRI) data, including four imaging...

The BraTS2018 database is a continually evolving database with a total of 285 glioblastoma or low-grade gliomas subjects, comprising three consecutive subsets, i.e., 30 subjects...

The dataset consists of T1-weighted brain MRI images of patients, with manual segmentation of anatomical structures provided.

G-Ref is a dataset for referring image segmentation, comprising 104K referring language expressions for around 55K objects in about 27K images.

Building change detection using multi-temporal airborne LiDAR data

The lesion masks dataset is used for prostate cancer segmentation. It contains 299 lesions annotated by two residents and two experienced board-certified radiologists.

Brain tumor segmentation dataset used for training and evaluation of the proposed Squeeze Excitation Embedded Attention UNet (SEEA-UNet) model.