SOTAVerified

Medical Image Segmentation

Medical Image Segmentation is a computer vision task that involves dividing an medical image into multiple segments, where each segment represents a different object or structure of interest in the image. The goal of medical image segmentation is to provide a precise and accurate representation of the objects of interest within the image, typically for the purpose of diagnosis, treatment planning, and quantitative analysis.

( Image credit: IVD-Net )

Papers

Showing 51100 of 2089 papers

TitleStatusHype
Polyp-PVT: Polyp Segmentation with Pyramid Vision TransformersCode2
Robust Semi-supervised Multimodal Medical Image Segmentation via Cross Modality CollaborationCode2
Rethinking Boundary Detection in Deep Learning-Based Medical Image SegmentationCode2
SelfReg-UNet: Self-Regularized UNet for Medical Image SegmentationCode2
MobileUNETR: A Lightweight End-To-End Hybrid Vision Transformer For Efficient Medical Image SegmentationCode2
SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical ImagesCode2
MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated DatasetCode2
ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image SegmentationCode2
MSA^2Net: Multi-scale Adaptive Attention-guided Network for Medical Image SegmentationCode2
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image SegmentationCode2
Segmentation Loss OdysseyCode2
BRAU-Net++: U-Shaped Hybrid CNN-Transformer Network for Medical Image SegmentationCode2
Medical Image Segmentation Review: The success of U-NetCode2
MedUniSeg: 2D and 3D Medical Image Segmentation via a Prompt-driven Universal ModelCode2
MSVM-UNet: Multi-Scale Vision Mamba UNet for Medical Image SegmentationCode2
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis AttentionCode2
M^2SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image SegmentationCode2
MedCLIP-SAM: Bridging Text and Image Towards Universal Medical Image SegmentationCode2
MIST: A Simple and Scalable End-To-End 3D Medical Imaging Segmentation FrameworkCode2
Leveraging Hallucinations to Reduce Manual Prompt Dependency in Promptable SegmentationCode2
LViT: Language meets Vision Transformer in Medical Image SegmentationCode2
MedCLIP-SAMv2: Towards Universal Text-Driven Medical Image SegmentationCode2
Multimodal Information Interaction for Medical Image SegmentationCode2
HMT-UNet: A hybird Mamba-Transformer Vision UNet for Medical Image SegmentationCode2
Are Vision xLSTM Embedded UNet More Reliable in Medical 3D Image Segmentation?Code2
Generative Medical SegmentationCode2
Generative AI Enables Medical Image Segmentation in Ultra Low-Data RegimesCode2
HiDiff: Hybrid Diffusion Framework for Medical Image SegmentationCode2
H-vmunet: High-order Vision Mamba UNet for Medical Image SegmentationCode2
Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image SegmentationCode2
FAMNet: Frequency-aware Matching Network for Cross-domain Few-shot Medical Image SegmentationCode2
LHU-Net: A Light Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Medical Image SegmentationCode2
3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentationCode2
mAIstro: an open-source multi-agentic system for automated end-to-end development of radiomics and deep learning models for medical imagingCode2
3D UX-Net: A Large Kernel Volumetric ConvNet Modernizing Hierarchical Transformer for Medical Image SegmentationCode2
FedFMS: Exploring Federated Foundation Models for Medical Image SegmentationCode2
EM-Net: Efficient Channel and Frequency Learning with Mamba for 3D Medical Image SegmentationCode2
Medical Image Segmentation with Domain Adaptation: A SurveyCode2
Adaptive Bidirectional Displacement for Semi-Supervised Medical Image SegmentationCode2
ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image SegmentationCode2
BEFUnet: A Hybrid CNN-Transformer Architecture for Precise Medical Image SegmentationCode2
Merging Context Clustering with Visual State Space Models for Medical Image SegmentationCode2
RevSAM2: Prompt SAM2 for Medical Image Segmentation via Reverse-Propagation without Fine-tuningCode2
Modality-agnostic Domain Generalizable Medical Image Segmentation by Multi-Frequency in Multi-Scale AttentionCode2
Diversified and Personalized Multi-rater Medical Image SegmentationCode2
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image SegmentationCode2
Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image SegmentationCode2
Noise-Consistent Siamese-Diffusion for Medical Image Synthesis and SegmentationCode2
Bidirectional Copy-Paste for Semi-Supervised Medical Image SegmentationCode2
Understanding the Tricks of Deep Learning in Medical Image Segmentation: Challenges and Future DirectionsCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DUCK-Netmean Dice0.95Unverified
2EffiSegNet-B5mean Dice0.95Unverified
3EffiSegNet-B4mean Dice0.95Unverified
4SegMedmean Dice0.95Unverified
5FCB Formermean Dice0.94Unverified
6FCB-SwinV2 Transformermean Dice0.94Unverified
7SEPmean Dice0.94Unverified
8LM-Netmean Dice0.94Unverified
9RAPUNetmean Dice0.94Unverified
10FCBFormermean Dice0.94Unverified
#ModelMetricClaimedVerifiedStatus
1DUCK-Netmean Dice0.97Unverified
2RAPUNetmean Dice0.96Unverified
3EMCADmean Dice0.95Unverified
4Yolo-SAM 2mean Dice0.95Unverified
5RaBiTmean Dice0.95Unverified
6UGCANetmean Dice0.95Unverified
7ESFPNet-Lmean Dice0.95Unverified
8FCBFormermean Dice0.95Unverified
9DuATmean Dice0.95Unverified
10SegMedmean Dice0.95Unverified
#ModelMetricClaimedVerifiedStatus
1RAPUNetmean Dice0.95Unverified
2DUCK-Netmean Dice0.94Unverified
3EMCADmean Dice0.92Unverified
4SegMedmean Dice0.92Unverified
5UniNetmean Dice0.92Unverified
6ProMISemean Dice0.87Unverified
7Meta-Polypmean Dice0.87Unverified
8ResUNet++ + TTAmean Dice0.85Unverified
9PVT-GCASCADEmean Dice0.83Unverified
10PVT-CASCADEmean Dice0.83Unverified
#ModelMetricClaimedVerifiedStatus
1RAPUNetmean Dice0.96Unverified
2SegMedmean Dice0.94Unverified
3DUCK-Netmean Dice0.94Unverified
4EMCADmean Dice0.92Unverified
5ProMISemean Dice0.84Unverified
6RSAFormermean Dice0.84Unverified
7ESFPNet-Lmean Dice0.82Unverified
8DuATmean Dice0.82Unverified
9PVT-CASCADEmean Dice0.8Unverified
10SSFormer-Lmean Dice0.8Unverified
#ModelMetricClaimedVerifiedStatus
1Interactive AI-SAM gt boxAvg DSC90.66Unverified
2Medical SAM AdapterAvg DSC89.8Unverified
3MedSegDiff-v2Avg DSC89.5Unverified
4nnUNetAvg DSC88.8Unverified
5MedNeXt-L (5x5x5)Avg DSC88.76Unverified
6MISTAvg DSC86.92Unverified
7nnFormerAvg DSC86.57Unverified
8AgileFormerAvg DSC86.11Unverified
9MERITAvg DSC84.9Unverified
10Automatic AI-SAMAvg DSC84.21Unverified
#ModelMetricClaimedVerifiedStatus
1FCTAvg DSC94.26Unverified
2Interactive AI-SAM gt boxAvg DSC93.89Unverified
3FCTAvg DSC93.02Unverified
4LHU-NetAvg DSC92.65Unverified
5MISTAvg DSC92.56Unverified
6MERITAvg DSC92.32Unverified
7MERIT-GCASCADEAvg DSC92.23Unverified
8EMCADAvg DSC92.12Unverified
9nnFormerAvg DSC92.06Unverified
10Automatic AI-SAMAvg DSC92.06Unverified
#ModelMetricClaimedVerifiedStatus
1StardistF184.6Unverified