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 751–775 of 2089 papers

Title	Date	Tasks	Status	Hype
A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends	Nov 30, 2023	Deep LearningImage Segmentation	CodeCode Available	0
Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation	Nov 30, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Alternate Diverse Teaching for Semi-supervised Medical Image Segmentation	Nov 29, 2023	Data AugmentationImage Segmentation	CodeCode Available	1
U-Net v2: Rethinking the Skip Connections of U-Net for Medical Image Segmentation	Nov 29, 2023	Computational EfficiencyDecoder	CodeCode Available	6
DEU-Net: Dual-Encoder U-Net for Automated Skin Lesion Segmentation	Nov 28, 2023	DecoderDiversity	CodeCode Available	1
I-MedSAM: Implicit Medical Image Segmentation with Segment Anything	Nov 28, 2023	DecoderImage Segmentation	CodeCode Available	1
Clean Label Disentangling for Medical Image Segmentation with Noisy Labels	Nov 28, 2023	DisentanglementImage Segmentation	CodeCode Available	0
Unleashing the Power of Prompt-driven Nucleus Instance Segmentation	Nov 27, 2023	Image SegmentationInstance Segmentation	CodeCode Available	1
Where to Begin? From Random to Foundation Model Instructed Initialization in Federated Learning for Medical Image Segmentation	Nov 27, 2023	Federated LearningImage Segmentation	—Unverified	0
Only Positive Cases: 5-fold High-order Attention Interaction Model for Skin Segmentation Derived Classification	Nov 27, 2023	Image SegmentationLesion Classification	CodeCode Available	1
Bayesian Neural Networks for 2D MRI Segmentation	Nov 24, 2023	Deep LearningImage Segmentation	—Unverified	0
LACFormer: Toward accurate and efficient polyp segmentation	Nov 23, 2023	DecoderImage Segmentation	CodeCode Available	0
SegVol: Universal and Interactive Volumetric Medical Image Segmentation	Nov 22, 2023	Computed Tomography (CT)Image Segmentation	CodeCode Available	2
FuseNet: Self-Supervised Dual-Path Network for Medical Image Segmentation	Nov 22, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
GMISeg: General Medical Image Segmentation without Re-Training	Nov 21, 2023	DecoderEnsemble Learning	—Unverified	0
Semi-supervised Medical Image Segmentation via Query Distribution Consistency	Nov 21, 2023	DecoderImage Segmentation	CodeCode Available	0
Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive Learning	Nov 21, 2023	Contrastive LearningImage Segmentation	CodeCode Available	0
Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation	Nov 21, 2023	Domain AdaptationMedical Image Analysis	CodeCode Available	1
Energy efficiency in Edge TPU vs. embedded GPU for computer-aided medical imaging segmentation and classification	Nov 20, 2023	ClassificationDiagnostic	—Unverified	0
SA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks	Nov 20, 2023	DiversityImage Segmentation	CodeCode Available	3
Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation	Nov 20, 2023	BenchmarkingImage Segmentation	—Unverified	0
On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation	Nov 18, 2023	Image SegmentationMedical Image Segmentation	—Unverified	0
WATUNet: A Deep Neural Network for Segmentation of Volumetric Sweep Imaging Ultrasound	Nov 17, 2023	DecoderImage Segmentation	—Unverified	0
MSE-Nets: Multi-annotated Semi-supervised Ensemble Networks for Improving Segmentation of Medical Image with Ambiguous Boundaries	Nov 17, 2023	Image SegmentationMedical Image Segmentation	—Unverified	0
Shifting to Machine Supervision: Annotation-Efficient Semi and Self-Supervised Learning for Automatic Medical Image Segmentation and Classification	Nov 17, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	0

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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