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Spot-the-difference
Spot-the-difference self-supervised pre-training for anomaly detection and segmentation. -
HGL: Hierarchical Geometry Learning for Test-time Adaptation in 3D Point Clou...
3D point cloud segmentation has received significant interest for its growing applications. However, the generalization ability of models suffers in dynamic scenarios due to the... -
Copy and paste augmentation for deformable wiring harness bags segmentation
The dataset is used for a study on copy-and-paste augmentation for deformable wiring harness bags segmentation. -
MyoPS dataset
The dataset used in the paper is the MyoPS dataset, which provides three-sequence Cardiac Magnetic Resonance (LGE, T2 and C0) and three anatomy masks, including myocardium... -
Image Segmentation
The Image Segmentation dataset is used to evaluate the performance of the ensemble average rule. -
Transparent Object Segmentation from Light-Field Images
Transparent object segmentation from light-field images. -
Internal Test Dataset
A dataset of 11 Positron Emission Tomography-CT (PET-CT) scans for bone marrow segmentation -
Custom Dataset for Subcutaneous Tissue Segmentation
A custom dataset consisting of hand-labeled images by an expert clinician and trainees are used for the experimentation, currently labeled into the following categories: skin,... -
AMOS22 CT subset
The AMOS22 CT subset is a large-scale abdominal multi-organ benchmark for versatile medical image segmentation. -
NIH pancreas segmentation dataset
The NIH pancreas segmentation dataset contains 82 abdominal CT volumes. The width and height of each volume are 512, while the axial view slice number can vary from 181 to 466.... -
ACDC Challenge
Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: Is the problem solved? -
Deep ensemble learning for segmenting tuberculosis-consistent manifestations ...
Automated segmentation of tuberculosis (TB)-consistent lesions in chest X-rays (CXRs) using deep learning (DL) methods can help reduce radiologist effort, supplement clinical... -
Automated Thalamic Nuclei Segmentation Using Multi-Planar Cascaded Convolutio...
A cascaded multi-planar scheme with a modified residual U-Net architecture was used to segment thalamic nuclei on conventional and white-matter-nulled (WMn) magnetization... -
BraTS 2021 dataset
The Brain Tumor Segmentation (BraTS) Challenge 2021 dataset, which provides a valuable resource for addressing challenges specific to resource-limited settings, particularly the... -
ACDC and M&Ms datasets
The dataset used for cardiac MRI segmentation -
PH2 dataset
The PH2 dataset used for evaluation of the proposed deep learning model for automatic skin lesion segmentation on dermoscopic images. -
PanNuke dataset
The PanNuke dataset comprises H&E stained images with a resolution of 256×256 pixels, totaling 7,904 images from 19 different tissue types. -
Osteoarthritis Initiative (OAI) dataset
Knee OsteoArthritis (KOA) dataset used for early detection of KOA (KL-0 vs KL-2) using Vision Transformer (ViT) model with selective shuffled position embedding and key-patch...
