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Medical Image Analysis and Classification
The dataset is used for medical image analysis and classification. -
Atrial Segmentation Challenge dataset
Semantic object segmentation is a fundamental task in medical image analysis and has been widely used in automatic delineation of regions of interest in 3D medical images, such... -
Medical Decathlon
A large annotated medical image dataset for the development and evaluation of segmentation algorithms. -
FDNet: Feature Decoupled Segmentation Network for Tooth CBCT Image
Precise Tooth Cone Beam Computed Tomography (CBCT) image segmentation is crucial for orthodontic treatment planning. In this paper, we propose FDNet, a Feature Decoupled... -
LiTS Liver Tumor Segmentation Challenge
Liver and tumor segmentation from Computed Tomography (CT) images is a mandatory task in diagnosing, monitoring, and treating liver diseases. -
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT im...
Automated liver tumor segmentation from Computed Tomography (CT) images is a necessary prerequisite in the interventions of hepatic abnormalities and surgery planning. -
EXACT'09 dataset
The EXACT'09 dataset is a multi-center, public dataset of airway extraction challenge. -
Swin Deformable Attention U-Net Transformer (SDAUT) for Explainable Fast MRI
Fast MRI aims to reconstruct a high fidelity image from partially observed measurements. Exuberant development in fast MRI using deep learning has been witnessed recently.... -
ACDC Challenge
Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: Is the problem solved? -
Anatomical Tracings of Lesions After Stroke (ATLAS)
The Anatomical Tracings of Lesions After Stroke (ATLAS) dataset is a collection of 229 T1-weighted normalized 3D MR images with diverse lesions manually segmented by specialists. -
RIGA+ dataset
The RIGA+ dataset is a multi-domain joint optic disc (OD) / optic cup (OC) segmentation dataset annotated by six ophthalmologists. -
BraTS 2020
Automatic segmentation of brain tumors is an essential but challenging step for extracting quantitative imaging biomarkers for accurate tumor detection, diagnosis, prognosis,... -
MICCAI BRATS dataset
The MICCAI BRATS dataset is a fully-annotated dataset for brain tumor segmentation. It contains 220 high-grade subjects and 54 low-grade subjects with four modalities: T1, T1c,... -
Medical Segmentation Decathlon (MSD) - prostate dataset
The Medical Segmentation Decathlon (MSD) - prostate dataset comprises of 48 (training =32, testing =16) multimodal (T2, ADC) 3D MRI samples.
