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PET-CT lymphoma dataset
The PET-CT dataset contains 3D images from 173 patients who were diagnosed with large B-cell lymphomas and underwent PET-CT examination. -
Microscopy Images
Microscopy Images dataset was from the NeurIPS 2022 Cell Segmentation Challenge [34] that focused on cell segmentation in various microscopy images. -
Endoscopy Images
Endoscopy images dataset was from the MICCAI 2017 EndoVis Challenge [1] that focused on segmenting seven instruments from endoscopy images. -
Abdomen MRI
Abdomen MRI dataset was from the MICCAI 2022 AMOS Challenge [25] that also focused on abdominal organ segmentation. -
Abdomen CT
Abdomen CT dataset was from the MICCAI 2022 FLARE Challenge [35] that focused on the segmentation of 13 abdominal organs, including the liver, spleen, pancreas, right kidney,... -
Medical Image Segmentation dataset
The dataset contains images of medical images and corresponding labels. -
Multi-Atlas Labeling Beyond the Cranial Vault (BTCV)
The BTCV dataset contains abdominal CT images for segmentation tasks. -
Abdominal Multi Organ Segmentation 2022 (AMOS2022) challenge dataset
The Abdominal Multi Organ Segmentation 2022 (AMOS2022) challenge dataset contains 500 CT and 100 MRI scans collected from multiple sites, a wide range of imaging conditions, and... -
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... -
ISBI 2013 Challenge
The ISBI 2013 challenge dataset is a collection of medical images with corresponding segmentations. -
Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata
Medical image segmentation with Deep Learning. This requirement makes it difficult to run state-of-the-art segmentation models in resource-constrained scenarios like primary... -
Amos: A large-scale abdominal multi-organ benchmark for versatile medical ima...
A large-scale abdominal multi-organ benchmark for versatile medical image segmentation -
Prostate MR and Abdominal CT
Two large multiclass data sets for prostate MR and abdominal CT -
MaskSAM: Towards Auto-prompt SAM with Mask Classification for Medical Image S...
Segment Anything Model (SAM) is a prompt-driven foundation model for natural image segmentation, which is trained on the large-scale SA-1B dataset of 1B masks and 11M images. -
Swin-Unet: Unet-like pure transformer for medical image segmentation
Swin-Unet: Unet-like pure transformer for medical image segmentation. -
Medical Transformer: Gated axial-attention for medical image segmentation
Medical Transformer: Gated axial-attention for medical image segmentation. -
Unet++: A nested U-Net architecture for medical image segmentation
Unet++: A nested U-Net architecture for medical image segmentation. -
Federated Data Model
Medical image segmentation task using cardiac magnetic resonance images from different hospitals.
