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 651–675 of 2089 papers

Title	Date	Tasks	Status	Hype
Efficient Medical Image Segmentation Based on Knowledge Distillation	Aug 23, 2021	Image SegmentationKnowledge Distillation	CodeCode Available	1
FCN-Transformer Feature Fusion for Polyp Segmentation	Aug 17, 2022	Lesion DetectionMedical Image Segmentation	CodeCode Available	1
AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation	Jun 16, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available	1
HiFormer: Hierarchical Multi-scale Representations Using Transformers for Medical Image Segmentation	Jul 18, 2022	DecoderImage Segmentation	CodeCode Available	1
HemSeg-200: A Voxel-Annotated Dataset for Intracerebral Hemorrhages Segmentation in Brain CT Scans	May 23, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Background Matters: A Cross-view Bidirectional Modeling Framework for Semi-supervised Medical Image Segmentation	May 22, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available	1
CA-Net: Comprehensive Attention Convolutional Neural Networks for Explainable Medical Image Segmentation	Sep 22, 2020	Image SegmentationLesion Segmentation	CodeCode Available	1
EffiDec3D: An Optimized Decoder for High-Performance and Efficient 3D Medical Image Segmentation	Jan 1, 2025	DecoderImage Segmentation	CodeCode Available	1
EffiSegNet: Gastrointestinal Polyp Segmentation through a Pre-Trained EfficientNet-based Network with a Simplified Decoder	Jul 23, 2024	DecoderImage Segmentation	CodeCode Available	1
High-Resolution Swin Transformer for Automatic Medical Image Segmentation	Jul 23, 2022	Brain Tumor SegmentationDecoder	CodeCode Available	1
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation	Sep 27, 2018	Image SegmentationMedical Image Segmentation	CodeCode Available	1
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
A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation	Apr 5, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Deep evidential fusion with uncertainty quantification and contextual discounting for multimodal medical image segmentation	Sep 12, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
DiffBoost: Enhancing Medical Image Segmentation via Text-Guided Diffusion Model	Oct 19, 2023	Data AugmentationImage Generation	CodeCode Available	1
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
On-the-Fly Test-time Adaptation for Medical Image Segmentation	Mar 10, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available	1
On uncertainty estimation in active learning for image segmentation	Jul 13, 2020	Active LearningImage Segmentation	CodeCode Available	1
Orthogonal Annotation Benefits Barely-supervised Medical Image Segmentation	Mar 23, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Paced-Curriculum Distillation with Prediction and Label Uncertainty for Image Segmentation	Feb 2, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images	Mar 14, 2024	3D Medical Imaging SegmentationGPU	CodeCode Available	1
Mutual Consistency Learning for Semi-supervised Medical Image Segmentation	Sep 21, 2021	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Cardiac Segmentation with Strong Anatomical Guarantees	Jun 15, 2020	Cardiac SegmentationImage Segmentation	CodeCode Available	1
Federated Cross Learning for Medical Image Segmentation	Apr 5, 2022	Ensemble LearningFederated Learning	CodeCode Available	1
1M parameters are enough? A lightweight CNN-based model for medical image segmentation	Jun 28, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1

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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