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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1301–1350 of 2089 papers

TitleStatusHype
Continuous U-Net: Faster, Greater and Noiseless—0
Contrastive Domain Disentanglement for Generalizable Medical Image Segmentation—0
Contrastive Re-localization and History Distillation in Federated CMR Segmentation—0
Contrastive Semi-Supervised Learning for 2D Medical Image Segmentation—0
ConvFormer: Combining CNN and Transformer for Medical Image Segmentation—0
Convolutional neural networks for medical image segmentation—0
Domain specific cues improve robustness of deep learning based segmentation of ct volumes—0
Convolution-Free Medical Image Segmentation using Transformers—0
Correlation Weighted Prototype-based Self-Supervised One-Shot Segmentation of Medical Images—0
CoSAM: Self-Correcting SAM for Domain Generalization in 2D Medical Image Segmentation—0
COSMOS: Cross-Modality Unsupervised Domain Adaptation for 3D Medical Image Segmentation based on Target-aware Domain Translation and Iterative Self-Training—0
COSST: Multi-organ Segmentation with Partially Labeled Datasets Using Comprehensive Supervisions and Self-training—0
Coupling AI and Citizen Science in Creation of Enhanced Training Dataset for Medical Image Segmentation—0
COVID-19 Chest CT Image Segmentation -- A Deep Convolutional Neural Network Solution—0
CRIS: Collaborative Refinement Integrated with Segmentation for Polyp Segmentation—0
CRISP - Reliable Uncertainty Estimation for Medical Image Segmentation—0
Critical Assessment of Transfer Learning for Medical Image Segmentation with Fully Convolutional Neural Networks—0
Cross-adversarial local distribution regularization for semi-supervised medical image segmentation—0
Cross-denoising Network against Corrupted Labels in Medical Image Segmentation with Domain Shift—0
Cross-Frequency Collaborative Training Network and Dataset for Semi-supervised First Molar Root Canal Segmentation—0
Cross-modality Knowledge Transfer for Prostate Segmentation from CT Scans—0
Cross-Modal Self-Attention Distillation for Prostate Cancer Segmentation—0
Cross-model Mutual Learning for Exemplar-based Medical Image Segmentation—0
Few-shot Medical Image Segmentation via Cross-Reference Transformer—0
Cross-supervised Dual Classifiers for Semi-supervised Medical Image Segmentation—0
CT Image Synthesis Using Weakly Supervised Segmentation and Geometric Inter-Label Relations For COVID Image Analysis—0
CT Synthesis with Conditional Diffusion Models for Abdominal Lymph Node Segmentation—0
CUAB: Convolutional Uncertainty Attention Block Enhanced the Chest X-ray Image Analysis—0
Cutting-Splicing data augmentation: A novel technology for medical image segmentation—0
D2-MLP: Dynamic Decomposed MLP Mixer for Medical Image Segmentation—0
Data-Centric Diet: Effective Multi-center Dataset Pruning for Medical Image Segmentation—0
Data-Driven Deep Supervision for Medical Image Segmentation—0
Data Efficient Unsupervised Domain Adaptation for Cross-Modality Image Segmentation—0
Data variation-aware medical image segmentation—0
Day-Night Adaptation: An Innovative Source-free Adaptation Framework for Medical Image Segmentation—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
Deep-ASPECTS: A Segmentation-Assisted Model for Stroke Severity Measurement—0
Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation—0
Deep Compatible Learning for Partially-Supervised Medical Image Segmentation—0
Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation—0
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation—0
Deep feature transfer between localization and segmentation tasks—0
Deep Generative Model-based Quality Control for Cardiac MRI Segmentation—0
Deep Label Fusion: A 3D End-to-End Hybrid Multi-Atlas Segmentation and Deep Learning Pipeline—0
Deep learning and its application to medical image segmentation—0
Deep learning architectures for automated image segmentation—0
Deep Learning-based Bio-Medical Image Segmentation using UNet Architecture and Transfer Learning—0
Deep Learning for Medical Image Processing: Overview, Challenges and Future—0
Deep Learning for Medical Image Segmentation—0
Expert-Adaptive Medical Image Segmentation—0
Show:102550
← PrevPage 27 of 42Next →
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