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 601650 of 2089 papers

TitleStatusHype
Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric MRICode1
BDG-Net: Boundary Distribution Guided Network for Accurate Polyp SegmentationCode1
Boundary loss for highly unbalanced segmentationCode1
Enhancing Weakly Supervised 3D Medical Image Segmentation through Probabilistic-aware LearningCode1
DOMINO: Domain-aware Model Calibration in Medical Image SegmentationCode1
MatchSeg: Towards Better Segmentation via Reference Image MatchingCode1
HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image SegmentationCode1
3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching between 3D and 2D NetworksCode1
Evidence fusion with contextual discounting for multi-modality medical image segmentationCode1
Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation?Code1
EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified DecoderCode1
High-Resolution Swin Transformer for Automatic Medical Image SegmentationCode1
HRMedSeg: Unlocking High-resolution Medical Image segmentation via Memory-efficient Attention ModelingCode1
DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image SegmentationCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
Medical Image Segmentation with InTEnt: Integrated Entropy Weighting for Single Image Test-Time AdaptationCode1
Improving Aleatoric Uncertainty Quantification in Multi-Annotated Medical Image Segmentation with Normalizing FlowsCode1
Dual Cross-Attention for Medical Image SegmentationCode1
Deep learning in magnetic resonance prostate segmentation: A review and a new perspectiveCode1
MediViSTA: Medical Video Segmentation via Temporal Fusion SAM Adaptation for EchocardiographyCode1
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised SegmentationCode1
HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPSCode1
GuidedNet: Semi-Supervised Multi-Organ Segmentation via Labeled Data Guide Unlabeled DataCode1
MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp SegmentationCode1
Dual-Task Mutual Learning for Semi-Supervised Medical Image SegmentationCode1
Brain Tumor Segmentation with Deep Neural NetworksCode1
HarDNet-DFUS: An Enhanced Harmonically-Connected Network for Diabetic Foot Ulcer Image Segmentation and Colonoscopy Polyp SegmentationCode1
DuAT: Dual-Aggregation Transformer Network for Medical Image SegmentationCode1
MEW-UNet: Multi-axis representation learning in frequency domain for medical image segmentationCode1
EViT-Unet: U-Net Like Efficient Vision Transformer for Medical Image Segmentation on Mobile and Edge DevicesCode1
Duo-SegNet: Adversarial Dual-Views for Semi-Supervised Medical Image SegmentationCode1
DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image SegmentationCode1
Harmonizing Pathological and Normal Pixels for Pseudo-healthy SynthesisCode1
MISm: A Medical Image Segmentation Metric for Evaluation of weak labeled DataCode1
Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 ChallengesCode1
E1D3 U-Net for Brain Tumor Segmentation: Submission to the RSNA-ASNR-MICCAI BraTS 2021 ChallengeCode1
E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image SegmentationCode1
BATFormer: Towards Boundary-Aware Lightweight Transformer for Efficient Medical Image SegmentationCode1
Gradient Alignment Improves Test-Time Adaptation for Medical Image SegmentationCode1
Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image SegmentationCode1
C3S3: Complementary Competition and Contrastive Selection for Semi-Supervised Medical Image SegmentationCode1
Exploring Smoothness and Class-Separation for Semi-supervised Medical Image SegmentationCode1
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With SupervoxelsCode1
GMSRF-Net: An improved generalizability with global multi-scale residual fusion network for polyp segmentationCode1
Effect of Prior-based Losses on Segmentation Performance: A BenchmarkCode1
Modality-Projection Universal Model for Comprehensive Full-Body Medical Imaging SegmentationCode1
Gradient-based Parameter Selection for Efficient Fine-TuningCode1
Graph Flow: Cross-layer Graph Flow Distillation for Dual Efficient Medical Image SegmentationCode1
A Deep Learning-based Quality Assessment and Segmentation System with a Large-scale Benchmark Dataset for Optical Coherence Tomographic Angiography ImageCode1
HemSeg-200: A Voxel-Annotated Dataset for Intracerebral Hemorrhages Segmentation in Brain CT ScansCode1
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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