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 1001–1050 of 2089 papers

TitleStatusHype
Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detection—0
Retinal Vessel Segmentation with Deep Graph and Capsule Reasoning—0
Fuse4Seg: Image-Level Fusion Based Multi-Modality Medical Image Segmentation—0
Learning Semi-Supervised Medical Image Segmentation from Spatial RegistrationCode0
Universal Topology Refinement for Medical Image Segmentation with Polynomial Feature Synthesis—0
Spectral U-Net: Enhancing Medical Image Segmentation via Spectral Decomposition—0
Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images—0
D2-MLP: Dynamic Decomposed MLP Mixer for Medical Image Segmentation—0
AFFSegNet: Adaptive Feature Fusion Segmentation Network for Microtumors and Multi-Organ SegmentationCode0
Effective Segmentation of Post-Treatment Gliomas Using Simple Approaches: Artificial Sequence Generation and Ensemble Models—0
Lagrange Duality and Compound Multi-Attention Transformer for Semi-Supervised Medical Image SegmentationCode0
SX-Stitch: An Efficient VMS-UNet Based Framework for Intraoperative Scoliosis X-Ray Image Stitching—0
FIF-UNet: An Efficient UNet Using Feature Interaction and Fusion for Medical Image Segmentation—0
Deep Self-Cleansing for Medical Image Segmentation with Noisy Labels—0
Medical Image Segmentation via Single-Source Domain Generalization with Random Amplitude Spectrum SynthesisCode0
Boundary feature fusion network for tooth image segmentation—0
Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image SegmentationCode0
TBConvL-Net: A Hybrid Deep Learning Architecture for Robust Medical Image Segmentation—0
TG-LMM: Enhancing Medical Image Segmentation Accuracy through Text-Guided Large Multi-Modal Model—0
Coupling AI and Citizen Science in Creation of Enhanced Training Dataset for Medical Image Segmentation—0
TransDAE: Dual Attention Mechanism in a Hierarchical Transformer for Efficient Medical Image Segmentation—0
A Novel Hybrid Parameter-Efficient Fine-Tuning Approach for Hippocampus Segmentation and Alzheimer's Disease Diagnosis—0
MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM—0
Curriculum Prompting Foundation Models for Medical Image SegmentationCode0
Language-guided Scale-aware MedSegmentor for Lesion Segmentation in Medical Imaging—0
Generalization Capabilities of Neural Cellular Automata for Medical Image Segmentation: A Robust and Lightweight Approach—0
ShapeMamba-EM: Fine-Tuning Foundation Model with Local Shape Descriptors and Mamba Blocks for 3D EM Image Segmentation—0
Few-Shot 3D Volumetric Segmentation with Multi-Surrogate Fusion—0
PAM: A Propagation-Based Model for Segmenting Any 3D Objects across Multi-Modal Medical Images—0
CNN-Transformer Rectified Collaborative Learning for Medical Image Segmentation—0
Size Aware Cross-shape Scribble Supervision for Medical Image Segmentation—0
From Few to More: Scribble-based Medical Image Segmentation via Masked Context Modeling and Continuous Pseudo Labels—0
FedGS: Federated Gradient Scaling for Heterogeneous Medical Image SegmentationCode0
Enhancing Cross-Modal Medical Image Segmentation through CompositionalityCode0
MedMAP: Promoting Incomplete Multi-modal Brain Tumor Segmentation with Alignment—0
Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models—0
Diffuse-UDA: Addressing Unsupervised Domain Adaptation in Medical Image Segmentation with Appearance and Structure Aligned Diffusion Models—0
Correlation Weighted Prototype-based Self-Supervised One-Shot Segmentation of Medical Images—0
Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation—0
Is SAM 2 Better than SAM in Medical Image Segmentation?—0
Novel adaptation of video segmentation to 3D MRI: efficient zero-shot knee segmentation with SAM2—0
Distillation Learning Guided by Image Reconstruction for One-Shot Medical Image SegmentationCode0
Biomedical SAM 2: Segment Anything in Biomedical Images and VideosCode0
Segmentation Style Discovery: Application to Skin Lesion ImagesCode0
Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
MedUHIP: Towards Human-In-the-Loop Medical Segmentation—0
Challenge Summary U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation—0
SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging SegmentationCode0
Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion TransformerCode0
Adaptive Mix for Semi-Supervised 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