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 751–800 of 2089 papers

TitleStatusHype
TransMedSeg: A Transferable Semantic Framework for Semi-Supervised Medical Image Segmentation—0
Mutual Evidential Deep Learning for Medical Image Segmentation—0
PRS-Med: Position Reasoning Segmentation with Vision-Language Model in Medical Imaging—0
Bridging the Inter-Domain Gap through Low-Level Features for Cross-Modal Medical Image SegmentationCode0
Rethinking the Mean Teacher Strategy from the Perspective of Self-paced Learning—0
DDFP: Data-dependent Frequency Prompt for Source Free Domain Adaptation of Medical Image SegmentationCode0
Data-Agnostic Augmentations for Unknown Variations: Out-of-Distribution Generalisation in MRI SegmentationCode0
BoundarySeg:An Embarrassingly Simple Method To Boost Medical Image Segmentation Performance for Low Data Regimes—0
Using Foundation Models as Pseudo-Label Generators for Pre-Clinical 4D Cardiac CT Segmentation—0
Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results—0
Skull stripping with purely synthetic dataCode0
Towards user-centered interactive medical image segmentation in VR with an assistive AI agent—0
Robust Kidney Abnormality Segmentation: A Validation Study of an AI-Based FrameworkCode0
BrainSegDMlF: A Dynamic Fusion-enhanced SAM for Brain Lesion Segmentation—0
DFEN: Dual Feature Equalization Network for Medical Image SegmentationCode0
Advancing 3D Medical Image Segmentation: Unleashing the Potential of Planarian Neural Networks in Artificial Intelligence—0
Adversarial Robustness Analysis of Vision-Language Models in Medical Image SegmentationCode0
UNet-3D with Adaptive TverskyCE Loss for Pancreas Medical Image Segmentation—0
SAM-Guided Robust Representation Learning for One-Shot 3D Medical Image Segmentation—0
RadSAM: Segmenting 3D radiological images with a 2D promptable model—0
NUDF: Neural Unsigned Distance Fields for high resolution 3D medical image segmentation—0
Performance Estimation for Supervised Medical Image Segmentation Models on Unlabeled Data Using UniverSeg—0
SuperCL: Superpixel Guided Contrastive Learning for Medical Image Segmentation Pre-training—0
WT-BCP: Wavelet Transform based Bidirectional Copy-Paste for Semi-Supervised Medical Image SegmentationCode0
Med-2D SegNet: A Light Weight Deep Neural Network for Medical 2D Image Segmentation—0
Efficient Parameter Adaptation for Multi-Modal Medical Image Segmentation and Prognosis—0
Putting the Segment Anything Model to the Test with 3D Knee MRI - A Comparison with State-of-the-Art PerformanceCode0
Cross-Frequency Collaborative Training Network and Dataset for Semi-supervised First Molar Root Canal Segmentation—0
TextDiffSeg: Text-guided Latent Diffusion Model for 3d Medical Images Segmentation—0
From Gaze to Insight: Bridging Human Visual Attention and Vision Language Model Explanation for Weakly-Supervised Medical Image SegmentationCode0
Efficient Medical Image Restoration via Reliability Guided Learning in Frequency Domain—0
HDC: Hierarchical Distillation for Multi-level Noisy Consistency in Semi-Supervised Fetal Ultrasound Segmentation—0
Mixture-of-Shape-Experts (MoSE): End-to-End Shape Dictionary Framework to Prompt SAM for Generalizable Medical Segmentation—0
Multi-Modal Brain Tumor Segmentation via 3D Multi-Scale Self-attention and Cross-attention—0
A Unified Loss for Handling Inter-Class and Intra-Class Imbalance in Medical Image SegmentationCode0
SynthFM: Training Modality-agnostic Foundation Models for Medical Image Segmentation without Real Medical Data—0
Do Segmentation Models Understand Vascular Structure? A Blob-Based XAI Framework—0
PRAD: Periapical Radiograph Analysis Dataset and Benchmark Model Development—0
Zeus: Zero-shot LLM Instruction for Union Segmentation in Multimodal Medical Imaging—0
Rethinking the Nested U-Net Approach: Enhancing Biomarker Segmentation with Attention Mechanisms and Multiscale Feature FusionCode0
Explaining Uncertainty in Multiple Sclerosis Lesion Segmentation Beyond Prediction Errors—0
Here Comes the Explanation: A Shapley Perspective on Multi-contrast Medical Image Segmentation—0
Performance Analysis of Deep Learning Models for Femur Segmentation in MRI Scan—0
Multi-encoder nnU-Net outperforms Transformer models with self-supervised pretraining—0
Multi-Granularity Vision Fastformer with Fusion Mechanism for Skin Lesion Segmentation—0
Agglomerating Large Vision Encoders via Distillation for VFSS Segmentation—0
SelfMedHPM: Self Pre-training With Hard Patches Mining Masked Autoencoders For Medical Image Segmentation—0
Test-time Adaptation for Foundation Medical Segmentation Model without Parametric Updates—0
Deconver: A Deconvolutional Network for Medical Image SegmentationCode0
Balancing Multi-Target Semi-Supervised Medical Image Segmentation with Collaborative Generalist and Specialists—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
9SegMedmean Dice0.95—Unverified
10DuATmean 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
9Automatic AI-SAMAvg DSC92.06—Unverified
10nnFormerAvg DSC92.06—Unverified
#ModelMetricClaimedVerifiedStatus
1StardistF184.6—Unverified