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

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Showing 501–550 of 2089 papers

TitleStatusHype
FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation CompletenessCode0
Domain Influence in MRI Medical Image Segmentation: spatial versus k-space inputsCode0
xLSTM-UNet can be an Effective 2D & 3D Medical Image Segmentation Backbone with Vision-LSTM (ViL) better than its Mamba CounterpartCode3
pFLFE: Cross-silo Personalized Federated Learning via Feature Enhancement on Medical Image Segmentation—0
AstMatch: Adversarial Self-training Consistency Framework for Semi-Supervised Medical Image SegmentationCode0
Robustness Testing of Black-Box Models Against CT Degradation Through Test-Time Augmentation—0
Segment Anything Model for automated image data annotation: empirical studies using text prompts from Grounding DINO—0
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text CuesCode1
Towards Synchronous Memorizability and Generalizability with Site-Modulated Diffusion Replay for Cross-Site Continual SegmentationCode0
Few-Shot Medical Image Segmentation with High-Fidelity PrototypesCode1
Stable Diffusion Segmentation for Biomedical Images with Single-step Reverse ProcessCode2
Domain Adaptation of Echocardiography Segmentation Via Reinforcement LearningCode1
Test-Time Generative Augmentation for Medical Image SegmentationCode1
Medical Image Segmentation Using Directional Window AttentionCode0
Multi-Aperture Fusion of Transformer-Convolutional Network (MFTC-Net) for 3D Medical Image Segmentation and VisualizationCode0
Are Vision xLSTM Embedded UNet More Reliable in Medical 3D Image Segmentation?Code2
Demystifying the Effect of Receptive Field Size in U-Net Models for Medical Image SegmentationCode0
Self-Supervised Alignment Learning for Medical Image Segmentation—0
SAM-EG: Segment Anything Model with Egde Guidance framework for efficient Polyp Segmentation—0
SelfReg-UNet: Self-Regularized UNet for Medical Image SegmentationCode2
Perspective+ Unet: Enhancing Segmentation with Bi-Path Fusion and Efficient Non-Local Attention for Superior Receptive FieldsCode1
FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation—0
CriDiff: Criss-cross Injection Diffusion Framework via Generative Pre-train for Prostate SegmentationCode1
Trusting Semantic Segmentation Networks—0
Low-Rank Mixture-of-Experts for Continual Medical Image Segmentation—0
An Empirical Study on the Fairness of Foundation Models for Multi-Organ Image Segmentation—0
Discriminative Hamiltonian Variational Autoencoder for Accurate Tumor Segmentation in Data-Scarce Regimes—0
ALPS: An Auto-Labeling and Pre-training Scheme for Remote Sensing Segmentation With Segment Anything ModelCode1
Boosting Medical Image Classification with Segmentation Foundation Model—0
Self Pre-training with Topology- and Spatiality-aware Masked Autoencoders for 3D Medical Image Segmentation—0
Enhancing Incomplete Multi-modal Brain Tumor Segmentation with Intra-modal Asymmetry and Inter-modal DependencyCode0
Spatial-Frequency Dual Progressive Attention Network For Medical Image SegmentationCode1
GCtx-UNet: Efficient Network for Medical Image SegmentationCode1
CAMS: Convolution and Attention-Free Mamba-based Cardiac Image SegmentationCode1
3D MRI Synthesis with Slice-Based Latent Diffusion Models: Improving Tumor Segmentation Tasks in Data-Scarce RegimesCode1
VISTA3D: Versatile Imaging SegmenTation and Annotation model for 3D Computed TomographyCode3
Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation—0
Multi-Task Multi-Scale Contrastive Knowledge Distillation for Efficient Medical Image SegmentationCode1
U-KAN Makes Strong Backbone for Medical Image Segmentation and GenerationCode2
Comparative Benchmarking of Failure Detection Methods in Medical Image Segmentation: Unveiling the Role of Confidence Aggregation—0
Interactive Image Selection and Training for Brain Tumor Segmentation Network—0
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation—0
Improving Segment Anything on the Fly: Auxiliary Online Learning and Adaptive Fusion for Medical Image Segmentation—0
SimSAM: Zero-shot Medical Image Segmentation via Simulated InteractionCode0
CRIS: Collaborative Refinement Integrated with Segmentation for Polyp Segmentation—0
CBAR‑UNet: A novel methodology for segmentation of cardiac magnetic resonance images using block attention‑based deep residual neural networkCode0
FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms—0
Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images—0
FRCNet Frequency and Region Consistency for Semi-supervised Medical Image Segmentation—0
A Classifier-Free Incremental Learning Framework for Scalable Medical Image Segmentation—0
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All datasetsKvasir-SEGCVC-ClinicDBCVC-ColonDBETIS-LARIBPOLYPDBSynapse multi-organ CTAutomatic Cardiac Diagnosis Challenge (ACDC)MoNuSeg2018 Data Science BowlGlaSBKAI-IGH NeoPolyp-SmallMICCAI 2015 Multi-Atlas Abdomen Labeling ChallengeACDC

Benchmark Results

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