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 1826–1850 of 2089 papers

Title	Date	Tasks	Status
Polyp-SES: Automatic Polyp Segmentation with Self-Enriched Semantic Model	Oct 2, 2024	Instance SegmentationMedical Image Segmentation	CodeCode Available
Medical Image Segmentation Using Directional Window Attention	Jun 25, 2024	Cell SegmentationDiagnostic	CodeCode Available
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition	Apr 15, 2024	Computational EfficiencyGPU	CodeCode Available
Post-Training Quantization for 3D Medical Image Segmentation: A Practical Study on Real Inference Engines	Jan 28, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available
Automated Segmentation and Connectivity Analysis for Normal Pressure Hydrocephalus	Jan 10, 2022	3D Medical Imaging SegmentationMedical Image Segmentation	CodeCode Available
Medical Image Segmentation Using Deep Learning: A Survey	Sep 28, 2020	Data AugmentationDeep Learning	CodeCode Available
MedCL: Learning Consistent Anatomy Distribution for Scribble-supervised Medical Image Segmentation	Mar 28, 2025	AnatomyClustering	CodeCode Available
STU-Net: Scalable and Transferable Medical Image Segmentation Models Empowered by Large-Scale Supervised Pre-training	Apr 13, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available
Predictive Accuracy-Based Active Learning for Medical Image Segmentation	May 1, 2024	Active LearningDiversity	CodeCode Available
MedAI: Transparency in Medical Image Segmentation	Nov 1, 2021	Image SegmentationMedical Image Segmentation	CodeCode Available
MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts	Jul 8, 2020	Image SegmentationMedical Image Segmentation	CodeCode Available
Mci-net: multi-scale context integrated network for liver ct image segmentation	May 3, 2023	2D Semantic SegmentationImage Segmentation	CodeCode Available
Autofocus Layer for Semantic Segmentation	May 22, 2018	Brain Tumor SegmentationMedical Image Segmentation	CodeCode Available
Style Content Decomposition-based Data Augmentation for Domain Generalizable Medical Image Segmentation	Feb 28, 2025	Data AugmentationImage Segmentation	CodeCode Available
Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion Transformer	Aug 1, 2024	DenoisingImage Segmentation	CodeCode Available
Manifold-Aware Local Feature Modeling for Semi-Supervised Medical Image Segmentation	Oct 14, 2024	Boundary DetectionImage Segmentation	CodeCode Available
M3DA: Benchmark for Unsupervised Domain Adaptation in 3D Medical Image Segmentation	Feb 24, 2025	Computed Tomography (CT)Domain Adaptation	CodeCode Available
Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models	Jul 1, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available
Autoadaptive Medical Segment Anything Model	Jul 2, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available
A Unified Loss for Handling Inter-Class and Intra-Class Imbalance in Medical Image Segmentation	Apr 11, 2025	Image SegmentationMedical Image Analysis	CodeCode Available
LoRA-PT: Low-Rank Adapting UNETR for Hippocampus Segmentation Using Principal Tensor Singular Values and Vectors	Jul 16, 2024	BraTS2021Hippocampus	CodeCode Available
LMBiS-Net: A Lightweight Multipath Bidirectional Skip Connection based CNN for Retinal Blood Vessel Segmentation	Sep 10, 2023	Computational EfficiencyImage Segmentation	CodeCode Available
Data-Agnostic Augmentations for Unknown Variations: Out-of-Distribution Generalisation in MRI Segmentation	May 15, 2025	Data AugmentationImage Segmentation	CodeCode Available
AdLER: Adversarial Training with Label Error Rectification for One-Shot Medical Image Segmentation	Sep 2, 2023	AnatomyData Augmentation	CodeCode Available
Linking convolutional neural networks with graph convolutional networks: application in pulmonary artery-vein separation	Sep 1, 2019	3D Medical Imaging SegmentationMedical Image 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