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 1951–1975 of 2089 papers

Title	Date	Tasks	Status
Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels	Dec 13, 2021	Ensemble LearningImage Segmentation	CodeCode Available
Hybrid Dual Mean-Teacher Network With Double-Uncertainty Guidance for Semi-Supervised Segmentation of MRI Scans	Mar 9, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available
Contrastive Learning with Temporal Correlated Medical Images: A Case Study using Lung Segmentation in Chest X-Rays	Sep 7, 2021	Contrastive LearningImage Segmentation	CodeCode Available
Contrastive and Selective Hidden Embeddings for Medical Image Segmentation	Jan 21, 2022	Contrastive Learningfeature selection	CodeCode Available
AFFSegNet: Adaptive Feature Fusion Segmentation Network for Microtumors and Multi-Organ Segmentation	Sep 12, 2024	DecoderImage Segmentation	CodeCode Available
Roughness Index and Roughness Distance for Benchmarking Medical Segmentation	Mar 23, 2021	BenchmarkingImage Segmentation	CodeCode Available
Constrained-CNN losses for weakly supervised segmentation	May 12, 2018	Medical Image SegmentationSegmentation	CodeCode Available
Towards Segment Anything Model (SAM) for Medical Image Segmentation: A Survey	May 5, 2023	BenchmarkingImage Generation	CodeCode Available
Confidence Contours: Uncertainty-Aware Annotation for Medical Semantic Segmentation	Aug 15, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available
How Reliable Are Out-of-Distribution Generalization Methods for Medical Image Segmentation?	Sep 3, 2021	HippocampusImage Segmentation	CodeCode Available
HistoSegNet: Semantic Segmentation of Histological Tissue Type in Whole Slide Images	Oct 1, 2019	DiagnosticMedical Image Segmentation	CodeCode Available
S2S2: Semantic Stacking for Robust Semantic Segmentation in Medical Imaging	Dec 17, 2024	DiversityImage Segmentation	CodeCode Available
S^3-Mamba: Small-Size-Sensitive Mamba for Lesion Segmentation	Dec 19, 2024	Image SegmentationLesion Segmentation	CodeCode Available
SafeClick: Error-Tolerant Interactive Segmentation of Any Medical Volumes via Hierarchical Expert Consensus	Jun 23, 2025	Image SegmentationInteractive Segmentation	CodeCode Available
ACCL: Adversarial constrained-CNN loss for weakly supervised medical image segmentation	May 1, 2020	Image SegmentationMedical Image Segmentation	CodeCode Available
Hi-gMISnet: generalized medical image segmentation using DWT based multilayer fusion and dual mode attention into high resolution pGAN	May 20, 2024	Generative Adversarial NetworkImage Segmentation	CodeCode Available
Heuristic Dropout: An Efficient Regularization Method for Medical Image Segmentation Models	May 23, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available
HELPNet: Hierarchical Perturbations Consistency and Entropy-guided Ensemble for Scribble Supervised Medical Image Segmentation	Dec 25, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available
HCDG: A Hierarchical Consistency Framework for Domain Generalization on Medical Image Segmentation	Sep 13, 2021	Data AugmentationDomain Generalization	CodeCode Available
SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided Prompting	Jun 24, 2025	Computed Tomography (CT)Image Segmentation	CodeCode Available
Achieving state-of-the-art performance in the Medical Out-of-Distribution (MOOD) challenge using plausible synthetic anomalies	Aug 2, 2023	Anomaly DetectionImage Segmentation	CodeCode Available
HALOS: Hallucination-free Organ Segmentation after Organ Resection Surgery	Mar 14, 2023	AnatomyDeep Learning	CodeCode Available
SAM-aware Test-time Adaptation for Universal Medical Image Segmentation	Jun 5, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available
SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation	Nov 19, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available
Going to Extremes: Weakly Supervised Medical Image Segmentation	Sep 25, 2020	BIG-bench Machine LearningImage Segmentation	CodeCode Available

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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