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 1376–1400 of 2089 papers

Title	Date	Tasks	Status
Distributed Contrastive Learning for Medical Image Segmentation	Aug 7, 2022	Contrastive LearningFederated Learning	—Unverified
Distribution-aware Margin Calibration for Medical Image Segmentation	Nov 3, 2020	Image SegmentationMedical Image Segmentation	—Unverified
Diversity-Promoting Ensemble for Medical Image Segmentation	Oct 22, 2022	DiversityImage Segmentation	—Unverified
FocusNet++: Attentive Aggregated Transformations for Efficient and Accurate Medical Image Segmentation	Dec 4, 2019	Image SegmentationMedical Image Segmentation	—Unverified
D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation	Dec 14, 2020	Image SegmentationLesion Segmentation	—Unverified
DmADs-Net: Dense multiscale attention and depth-supervised network for medical image segmentation	May 1, 2024	Image SegmentationMedical Image Segmentation	—Unverified
DMC-Net: Lightweight Dynamic Multi-Scale and Multi-Resolution Convolution Network for Pancreas Segmentation in CT Images	Oct 3, 2024	Image SegmentationMedical Image Segmentation	—Unverified
DMCNN: A Deep Multiscale Convolutional Neural Network Model for Medical Image Segmentation	Dec 27, 2019	Data AugmentationDecoder	—Unverified
Domain Adaptation Meets Zero-Shot Learning: An Annotation-Efficient Approach to Multi-Modality Medical Image Segmentation	Mar 19, 2022	Domain AdaptationImage Segmentation	—Unverified
Domain Game: Disentangle Anatomical Feature for Single Domain Generalized Segmentation	Jun 4, 2024	Brain Tumor SegmentationDiagnostic	—Unverified
Domain Generalization with Adversarial Intensity Attack for Medical Image Segmentation	Apr 5, 2023	DiversityDomain Generalization	—Unverified
Do Segmentation Models Understand Vascular Structure? A Blob-Based XAI Framework	Apr 11, 2025	Image SegmentationMedical Image Segmentation	—Unverified
Double Banking on Knowledge: Customized Modulation and Prototypes for Multi-Modality Semi-supervised Medical Image Segmentation	Oct 23, 2024	Contrastive LearningImage Segmentation	—Unverified
DoubleU-NetPlus: A Novel Attention and Context Guided Dual U-Net with Multi-Scale Residual Feature Fusion Network for Semantic Segmentation of Medical Images	Nov 25, 2022	Image SegmentationMedical Image Segmentation	—Unverified
Downstream Analysis of Foundational Medical Vision Models for Disease Progression	Mar 21, 2025	Image RegistrationImage Segmentation	—Unverified
DPE-Net: Dual-Parallel Encoder Based Network for Semantic Segmentation of Polyps	Dec 1, 2024	DiversityImage Segmentation	—Unverified
DRL-STNet: Unsupervised Domain Adaptation for Cross-modality Medical Image Segmentation via Disentangled Representation Learning	Sep 26, 2024	Domain AdaptationGPU	—Unverified
Dual Structure-Aware Image Filterings for Semi-supervised Medical Image Segmentation	Dec 12, 2023	Image SegmentationMedical Image Segmentation	—Unverified
Dual-Teacher: Integrating Intra-domain and Inter-domain Teachers for Annotation-efficient Cardiac Segmentation	Jul 13, 2020	Cardiac SegmentationDomain Adaptation	—Unverified
DyCON: Dynamic Uncertainty-aware Consistency and Contrastive Learning for Semi-supervised Medical Image Segmentation	Jan 1, 2025	Contrastive LearningImage Segmentation	—Unverified
Dynamically evolving segment anything model with continuous learning for medical image segmentation	Mar 8, 2025	DiversityImage Segmentation	—Unverified
EAA-Net: Rethinking the Autoencoder Architecture with Intra-class Features for Medical Image Segmentation	Aug 19, 2022	Image SegmentationMedical Image Segmentation	—Unverified
EAGLE: An Efficient Global Attention Lesion Segmentation Model for Hepatic Echinococcosis	Jun 25, 2025	Image SegmentationLesion Segmentation	—Unverified
EAUWSeg: Eliminating annotation uncertainty in weakly-supervised medical image segmentation	Jan 3, 2025	Image SegmentationMedical Image Segmentation	—Unverified
ECG Segmentation using a Neural Network as the Basis for Detection of Cardiac Pathologies	Apr 23, 2020	Medical DiagnosisMedical Image Segmentation	—Unverified

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All datasets Kvasir-SEG CVC-ClinicDB CVC-ColonDB ETIS-LARIBPOLYPDB Synapse multi-organ CT Automatic Cardiac Diagnosis Challenge (ACDC)MoNuSeg 2018 Data Science Bowl GlaS BKAI-IGH NeoPolyp-Small MICCAI 2015 Multi-Atlas Abdomen Labeling Challenge ACDC

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DUCK-Net	mean Dice	0.95	—	Unverified
2	EffiSegNet-B5	mean Dice	0.95	—	Unverified
3	EffiSegNet-B4	mean Dice	0.95	—	Unverified
4	SegMed	mean Dice	0.95	—	Unverified
5	FCB Former	mean Dice	0.94	—	Unverified
6	FCB-SwinV2 Transformer	mean Dice	0.94	—	Unverified
7	SEP	mean Dice	0.94	—	Unverified
8	LM-Net	mean Dice	0.94	—	Unverified
9	RAPUNet	mean Dice	0.94	—	Unverified
10	FCBFormer	mean Dice	0.94	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DUCK-Net	mean Dice	0.97	—	Unverified
2	RAPUNet	mean Dice	0.96	—	Unverified
3	EMCAD	mean Dice	0.95	—	Unverified
4	Yolo-SAM 2	mean Dice	0.95	—	Unverified
5	RaBiT	mean Dice	0.95	—	Unverified
6	UGCANet	mean Dice	0.95	—	Unverified
7	ESFPNet-L	mean Dice	0.95	—	Unverified
8	FCBFormer	mean Dice	0.95	—	Unverified
9	DuAT	mean Dice	0.95	—	Unverified
10	SegMed	mean Dice	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RAPUNet	mean Dice	0.95	—	Unverified
2	DUCK-Net	mean Dice	0.94	—	Unverified
3	EMCAD	mean Dice	0.92	—	Unverified
4	SegMed	mean Dice	0.92	—	Unverified
5	UniNet	mean Dice	0.92	—	Unverified
6	ProMISe	mean Dice	0.87	—	Unverified
7	Meta-Polyp	mean Dice	0.87	—	Unverified
8	ResUNet++ + TTA	mean Dice	0.85	—	Unverified
9	PVT-GCASCADE	mean Dice	0.83	—	Unverified
10	PVT-CASCADE	mean Dice	0.83	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RAPUNet	mean Dice	0.96	—	Unverified
2	SegMed	mean Dice	0.94	—	Unverified
3	DUCK-Net	mean Dice	0.94	—	Unverified
4	EMCAD	mean Dice	0.92	—	Unverified
5	ProMISe	mean Dice	0.84	—	Unverified
6	RSAFormer	mean Dice	0.84	—	Unverified
7	ESFPNet-L	mean Dice	0.82	—	Unverified
8	DuAT	mean Dice	0.82	—	Unverified
9	PVT-CASCADE	mean Dice	0.8	—	Unverified
10	SSFormer-L	mean Dice	0.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Interactive AI-SAM gt box	Avg DSC	90.66	—	Unverified
2	Medical SAM Adapter	Avg DSC	89.8	—	Unverified
3	MedSegDiff-v2	Avg DSC	89.5	—	Unverified
4	nnUNet	Avg DSC	88.8	—	Unverified
5	MedNeXt-L (5x5x5)	Avg DSC	88.76	—	Unverified
6	MIST	Avg DSC	86.92	—	Unverified
7	nnFormer	Avg DSC	86.57	—	Unverified
8	AgileFormer	Avg DSC	86.11	—	Unverified
9	MERIT	Avg DSC	84.9	—	Unverified
10	Automatic AI-SAM	Avg DSC	84.21	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FCT	Avg DSC	94.26	—	Unverified
2	Interactive AI-SAM gt box	Avg DSC	93.89	—	Unverified
3	FCT	Avg DSC	93.02	—	Unverified
4	LHU-Net	Avg DSC	92.65	—	Unverified
5	MIST	Avg DSC	92.56	—	Unverified
6	MERIT	Avg DSC	92.32	—	Unverified
7	MERIT-GCASCADE	Avg DSC	92.23	—	Unverified
8	EMCAD	Avg DSC	92.12	—	Unverified
9	nnFormer	Avg DSC	92.06	—	Unverified
10	Automatic AI-SAM	Avg DSC	92.06	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Stardist	F1	84.6	—	Unverified