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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 451–475 of 2089 papers

Title	Date	Tasks	Status	Hype	Score
Kvasir-Instrument: Diagnostic and therapeutic tool segmentation dataset in gastrointestinal endoscopy	Oct 23, 2020	BenchmarkingDiagnostic	CodeCode Available	1	5
LeViT-UNet: Make Faster Encoders with Transformer for Medical Image Segmentation	Jul 19, 2021	DecoderImage Segmentation	CodeCode Available	1	5
GMSRF-Net: An improved generalizability with global multi-scale residual fusion network for polyp segmentation	Nov 20, 2021	Decoderfeature selection	CodeCode Available	1	5
nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation	Apr 15, 2024	BenchmarkingImage Segmentation	CodeCode Available	1	5
Cross-head mutual Mean-Teaching for semi-supervised medical image segmentation	Oct 8, 2023	Data AugmentationImage Segmentation	CodeCode Available	1	5
Cross-level Contrastive Learning and Consistency Constraint for Semi-supervised Medical Image Segmentation	Feb 8, 2022	Contrastive LearningImage Segmentation	CodeCode Available	1	5
Gradient-based Parameter Selection for Efficient Fine-Tuning	Dec 15, 2023	image-classificationImage Classification	CodeCode Available	1	5
Graph Flow: Cross-layer Graph Flow Distillation for Dual Efficient Medical Image Segmentation	Mar 16, 2022	Image SegmentationKnowledge Distillation	CodeCode Available	1	5
CrossMatch: Enhance Semi-Supervised Medical Image Segmentation with Perturbation Strategies and Knowledge Distillation	May 1, 2024	Image SegmentationKnowledge Distillation	CodeCode Available	1	5
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation	Jan 8, 2022	Brain SegmentationDomain Adaptation	CodeCode Available	1	5
Cross-Modal Conditioned Reconstruction for Language-guided Medical Image Segmentation	Apr 3, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	1	5
IOP-FL: Inside-Outside Personalization for Federated Medical Image Segmentation	Apr 16, 2022	Federated LearningImage Segmentation	CodeCode Available	1	5
HarDNet-DFUS: An Enhanced Harmonically-Connected Network for Diabetic Foot Ulcer Image Segmentation and Colonoscopy Polyp Segmentation	Sep 15, 2022	DecoderImage Segmentation	CodeCode Available	1	5
Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label Fusion	Feb 4, 2022	Computational EfficiencyImage Registration	CodeCode Available	1	5
On-the-Fly Test-time Adaptation for Medical Image Segmentation	Mar 10, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available	1	5
On uncertainty estimation in active learning for image segmentation	Jul 13, 2020	Active LearningImage Segmentation	CodeCode Available	1	5
Cross Prompting Consistency with Segment Anything Model for Semi-supervised Medical Image Segmentation	Jul 7, 2024	DecoderImage Segmentation	CodeCode Available	1	5
AI-SAM: Automatic and Interactive Segment Anything Model	Dec 5, 2023	Medical Image SegmentationSemantic Segmentation	CodeCode Available	1	5
HarDNet-MSEG: A Simple Encoder-Decoder Polyp Segmentation Neural Network that Achieves over 0.9 Mean Dice and 86 FPS	Jan 18, 2021	DecoderGPU	CodeCode Available	1	5
CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation	Nov 8, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1	5
CSWin-UNet: Transformer UNet with Cross-Shaped Windows for Medical Image Segmentation	Jul 25, 2024	Computational EfficiencyDecoder	CodeCode Available	1	5
Automated segmentation of lesions and organs at risk on [68Ga]Ga-PSMA-11 PET/CT images using self-supervised learning with Swin UNETR	Feb 29, 2024	DecoderMedical Image Segmentation	CodeCode Available	1	5
A context based deep learning approach for unbalanced medical image segmentation	Jan 8, 2020	Deep LearningImage Segmentation	CodeCode Available	1	5
Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation	Feb 12, 2025	Computational EfficiencyImage Segmentation	CodeCode Available	1	5
An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation	Feb 1, 2022	3D Medical Imaging SegmentationImage Segmentation	CodeCode Available	1	5

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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