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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 1051–1100 of 2089 papers

TitleStatusHype
Robust Box Prompt based SAM for Medical Image Segmentation—0
Expanding the Medical Decathlon dataset: segmentation of colon and colorectal cancer from computed tomography imagesCode0
Distribution-Aware Replay for Continual MRI Segmentation—0
Robust Conformal Volume Estimation in 3D Medical ImagesCode0
Dense Self-Supervised Learning for Medical Image Segmentation—0
Channel Boosted CNN-Transformer-based Multi-Level and Multi-Scale Nuclei Segmentation—0
Few-Shot Medical Image Segmentation with Large Kernel Attention—0
How good nnU-Net for Segmenting Cardiac MRI: A Comprehensive Evaluation—0
Topology-Preserving Downsampling of Binary ImagesCode0
Segmentation by registration-enabled SAM prompt engineering using five reference imagesCode0
Trans2Unet: Neural fusion for Nuclei Semantic Segmentation—0
Navigating Uncertainty in Medical Image Segmentation—0
FDiff-Fusion:Denoising diffusion fusion network based on fuzzy learning for 3D medical image segmentation—0
MedSAGa: Few-shot Memory Efficient Medical Image Segmentation using Gradient Low-Rank Projection in SAM—0
LoRA-PT: Low-Rank Adapting UNETR for Hippocampus Segmentation Using Principal Tensor Singular Values and VectorsCode0
Efficient In-Context Medical Segmentation with Meta-driven Visual Prompt Selection—0
Enhancing Semantic Segmentation with Adaptive Focal Loss: A Novel Approach—0
Segmenting Medical Images with Limited DataCode0
SliceMamba with Neural Architecture Search for Medical Image Segmentation—0
S&D Messenger: Exchanging Semantic and Domain Knowledge for Generic Semi-Supervised Medical Image Segmentation—0
Interpretability of Uncertainty: Exploring Cortical Lesion Segmentation in Multiple SclerosisCode0
Enhancing Label-efficient Medical Image Segmentation with Text-guided Diffusion Models—0
Self-Paced Sample Selection for Barely-Supervised Medical Image SegmentationCode0
Leveraging Task-Specific Knowledge from LLM for Semi-Supervised 3D Medical Image Segmentation—0
SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation—0
Semi-Supervised Segmentation via Embedding Matching—0
FedIA: Federated Medical Image Segmentation with Heterogeneous Annotation CompletenessCode0
Domain Influence in MRI Medical Image Segmentation: spatial versus k-space inputsCode0
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
Segment Anything Model for automated image data annotation: empirical studies using text prompts from Grounding DINO—0
Robustness Testing of Black-Box Models Against CT Degradation Through Test-Time Augmentation—0
Towards Synchronous Memorizability and Generalizability with Site-Modulated Diffusion Replay for Cross-Site Continual SegmentationCode0
Medical Image Segmentation Using Directional Window AttentionCode0
Demystifying the Effect of Receptive Field Size in U-Net Models for Medical Image SegmentationCode0
Multi-Aperture Fusion of Transformer-Convolutional Network (MFTC-Net) for 3D Medical Image Segmentation and VisualizationCode0
Self-Supervised Alignment Learning for Medical Image Segmentation—0
SAM-EG: Segment Anything Model with Egde Guidance framework for efficient Polyp Segmentation—0
FIESTA: Fourier-Based Semantic Augmentation with Uncertainty Guidance for Enhanced Domain Generalizability in Medical Image Segmentation—0
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
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
Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation—0
Interactive Image Selection and Training for Brain Tumor Segmentation Network—0
Comparative Benchmarking of Failure Detection Methods in Medical Image Segmentation: Unveiling the Role of Confidence Aggregation—0
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized 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