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 1601–1650 of 2089 papers

TitleStatusHype
Learning to Learn Unlearned Feature for Brain Tumor Segmentation—0
Learning to segment fetal brain tissue from noisy annotations—0
Learning to Segment Medical Images with Scribble-Supervision Alone—0
Learning to Segment Skin Lesions from Noisy Annotations—0
Learning Transferable Object-Centric Diffeomorphic Transformations for Data Augmentation in Medical Image Segmentation—0
Learning with Limited Annotations: A Survey on Deep Semi-Supervised Learning for Medical Image Segmentation—0
Learn the new, keep the old: Extending pretrained models with new anatomy and images—0
Structurally Different Neural Network Blocks for the Segmentation of Atrial and Aortic Perivascular Adipose Tissue in Multi-centre CT Angiography Scans—0
Leveraging Fixed and Dynamic Pseudo-labels for Semi-supervised Medical Image Segmentation—0
Leveraging Global Binary Masks for Structure Segmentation in Medical Images—0
Leveraging Image Complexity in Macro-Level Neural Network Design for Medical Image Segmentation—0
Leveraging Task-Specific Knowledge from LLM for Semi-Supervised 3D Medical Image Segmentation—0
LIMIS: Towards Language-based Interactive Medical Image Segmentation—0
Limitations of Out-of-Distribution Detection in 3D Medical Image Segmentation—0
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation—0
Local-Global Pseudo-label Correction for Source-free Domain Adaptive Medical Image Segmentation—0
Localized Region Contrast for Enhancing Self-Supervised Learning in Medical Image Segmentation—0
Low-Rank Mixture-of-Experts for Continual Medical Image Segmentation—0
LSegDiff: A Latent Diffusion Model for Medical Image Segmentation—0
Language-guided Scale-aware MedSegmentor for Lesion Segmentation in Medical Imaging—0
L-SNet: from Region Localization to Scale Invariant Medical Image Segmentation—0
LSU-Net: Lightweight Automatic Organs Segmentation Network For Medical Images—0
LT-Net: Label Transfer by Learning Reversible Voxel-wise Correspondence for One-shot Medical Image Segmentation—0
Lumbar Spine Tumor Segmentation and Localization in T2 MRI Images Using AI—0
Lung nodules segmentation from CT with DeepHealth toolkit—0
M^2UNet: MetaFormer Multi-scale Upsampling Network for Polyp Segmentation—0
M3FPolypSegNet: Segmentation Network with Multi-frequency Feature Fusion for Polyp Localization in Colonoscopy Images—0
MAMBO-NET: Multi-Causal Aware Modeling Backdoor-Intervention Optimization for Medical Image Segmentation Network—0
MAPUNetR: A Hybrid Vision Transformer and U-Net Architecture for Efficient and Interpretable Medical Image Segmentation—0
Marginal Thresholding in Noisy Image Segmentation—0
Masked Image Modeling Advances 3D Medical Image Analysis—0
Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain—0
MaskSAM: Towards Auto-prompt SAM with Mask Classification for Medical Image Segmentation—0
MA-Unet: An improved version of Unet based on multi-scale and attention mechanism for medical image segmentation—0
Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation—0
MDFI-Net: Multiscale Differential Feature Interaction Network for Accurate Retinal Vessel Segmentation—0
Med-2D SegNet: A Light Weight Deep Neural Network for Medical 2D Image Segmentation—0
Med-DANet: Dynamic Architecture Network for Efficient Medical Volumetric Segmentation—0
MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation—0
Medical Image Analysis using Deep Relational Learning—0
Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes—0
Medical Image Segmentation on MRI Images with Missing Modalities: A Review—0
Medical Image Segmentation with 3D Convolutional Neural Networks: A Survey—0
Medical Image Segmentation Using a U-Net type of Architecture—0
Medical Image Segmentation using LeViT-UNet++: A Case Study on GI Tract Data—0
Medical Image Segmentation via Sparse Coding Decoder—0
Medical Image Segmentation with Belief Function Theory and Deep Learning—0
Medical image segmentation with imperfect 3D bounding boxes—0
Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models—0
Medical Image Segmentation with SAM-generated Annotations—0
Show:102550
← PrevPage 33 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