Medical Image Segmentation - Groups

ISIC 2016

Automated medical image segmentation can assist doctors to diagnose faster and more accurate. Deep learning based models for medical image segmentation have made great progress...

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DIAMANT

The DIAMANT dataset is a medical image segmentation dataset used to evaluate the proposed DIAMANT architecture.

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MICCAI 2019 StructSeg challenge dataset

The MICCAI 2019 StructSeg challenge dataset for GTV segmentation of nasopharynx cancer from CT images.

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TotalSegmentator-V2

The TotalSegmentator-V2 dataset is a publicly available dataset for 3D medical image segmentation. It contains 1,228 CT scans with annotations for 117 major anatomical...

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PromptNucSeg

A novel prompt-driven framework for automatic nucleus instance segmentation in histology images.

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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.

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Swin-Unet: Unet-like pure transformer for medical image segmentation

Swin-Unet: Unet-like pure transformer for medical image segmentation.

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Medical Transformer: Gated axial-attention for medical image segmentation

Medical Transformer: Gated axial-attention for medical image segmentation.

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Unet++: A nested U-Net architecture for medical image segmentation

Unet++: A nested U-Net architecture for medical image segmentation.

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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...

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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.

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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.

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SCGM dataset

The dataset used for training and testing the proposed deep co-training method for semi-supervised image segmentation.

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Federated Data Model

Medical image segmentation task using cardiac magnetic resonance images from different hospitals.

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MRI Spine Segmentation Dataset

The dataset used for training and validation of the EigenRank algorithm for data subset selection and failure prediction in deep learning based medical image segmentation.