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 1226–1250 of 2089 papers

Title	Date	Tasks	Status
A Survey on Deep Learning for Polyp Segmentation: Techniques, Challenges and Future Trends	Nov 30, 2023	Deep LearningImage Segmentation	CodeCode Available
Clean Label Disentangling for Medical Image Segmentation with Noisy Labels	Nov 28, 2023	DisentanglementImage Segmentation	CodeCode Available
Where to Begin? From Random to Foundation Model Instructed Initialization in Federated Learning for Medical Image Segmentation	Nov 27, 2023	Federated LearningImage Segmentation	—Unverified
Bayesian Neural Networks for 2D MRI Segmentation	Nov 24, 2023	Deep LearningImage Segmentation	—Unverified
LACFormer: Toward accurate and efficient polyp segmentation	Nov 23, 2023	DecoderImage Segmentation	CodeCode Available
GMISeg: General Medical Image Segmentation without Re-Training	Nov 21, 2023	DecoderEnsemble Learning	—Unverified
Semi-supervised Medical Image Segmentation via Query Distribution Consistency	Nov 21, 2023	DecoderImage Segmentation	CodeCode Available
Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive Learning	Nov 21, 2023	Contrastive LearningImage Segmentation	CodeCode Available
Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation	Nov 20, 2023	BenchmarkingImage Segmentation	—Unverified
Energy efficiency in Edge TPU vs. embedded GPU for computer-aided medical imaging segmentation and classification	Nov 20, 2023	ClassificationDiagnostic	—Unverified
On the Out of Distribution Robustness of Foundation Models in Medical Image Segmentation	Nov 18, 2023	Image SegmentationMedical Image Segmentation	—Unverified
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
Enhancing the Reliability of Segment Anything Model for Auto-Prompting Medical Image Segmentation with Uncertainty Rectification	Nov 17, 2023	Image SegmentationMedical Image Segmentation	—Unverified
SSASS: Semi-Supervised Approach for Stenosis Segmentation	Nov 17, 2023	Medical Image SegmentationPseudo Label	—Unverified
UniMOS: A Universal Framework For Multi-Organ Segmentation Over Label-Constrained Datasets	Nov 17, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available
WATUNet: A Deep Neural Network for Segmentation of Volumetric Sweep Imaging Ultrasound	Nov 17, 2023	DecoderImage Segmentation	—Unverified
End-to-end autoencoding architecture for the simultaneous generation of medical images and corresponding segmentation masks	Nov 17, 2023	Brain Tumor SegmentationData Augmentation	—Unverified
MPSeg : Multi-Phase strategy for coronary artery Segmentation	Nov 17, 2023	Coronary Artery SegmentationMedical Image Segmentation	—Unverified
Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation	Nov 17, 2023	DecoderImage Segmentation	CodeCode Available
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
Two-stage Joint Transductive and Inductive learning for Nuclei Segmentation	Nov 15, 2023	Image SegmentationInductive Learning	—Unverified
Robust semi-supervised segmentation with timestep ensembling diffusion models	Nov 13, 2023	DenoisingImage Segmentation	—Unverified
Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts	Nov 13, 2023	Image SegmentationInteractive Segmentation	CodeCode Available
PICS in Pics: Physics Informed Contour Selection for Rapid Image Segmentation	Nov 13, 2023	Image SegmentationMedical Image Segmentation	—Unverified
EviPrompt: A Training-Free Evidential Prompt Generation Method for Segment Anything Model in Medical Images	Nov 10, 2023	Image SegmentationMedical 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