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 1476–1500 of 2089 papers

Title	Date	Tasks	Status
Multi-rater Prism: Learning self-calibrated medical image segmentation from multiple raters	Dec 1, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available
Reducing Domain Gap in Frequency and Spatial domain for Cross-modality Domain Adaptation on Medical Image Segmentation	Nov 28, 2022	Domain AdaptationImage Segmentation	—Unverified
DoubleU-NetPlus: A Novel Attention and Context Guided Dual U-Net with Multi-Scale Residual Feature Fusion Network for Semantic Segmentation of Medical Images	Nov 25, 2022	Image SegmentationMedical Image Segmentation	—Unverified
Parameter-Efficient Transformer with Hybrid Axial-Attention for Medical Image Segmentation	Nov 17, 2022	feature selectionImage Segmentation	—Unverified
Convolutional neural networks for medical image segmentation	Nov 17, 2022	ClassificationImage Segmentation	—Unverified
A Point in the Right Direction: Vector Prediction for Spatially-aware Self-supervised Volumetric Representation Learning	Nov 15, 2022	Image SegmentationMedical Image Segmentation	—Unverified
Feedback Chain Network For Hippocampus Segmentation	Nov 15, 2022	Decoderfeature selection	—Unverified
Spatially Exclusive Pasting: A General Data Augmentation for the Polyp Segmentation	Nov 15, 2022	Data AugmentationMedical Image Segmentation	—Unverified
Unsupervised Feature Clustering Improves Contrastive Representation Learning for Medical Image Segmentation	Nov 15, 2022	ClusteringContrastive Learning	—Unverified
ConvFormer: Combining CNN and Transformer for Medical Image Segmentation	Nov 15, 2022	Image SegmentationMedical Image Segmentation	—Unverified
Knowledge Distillation from Cross Teaching Teachers for Efficient Semi-Supervised Abdominal Organ Segmentation in CT	Nov 11, 2022	Image SegmentationKnowledge Distillation	CodeCode Available
Improving Uncertainty-based Out-of-Distribution Detection for Medical Image Segmentation	Nov 10, 2022	Image SegmentationMedical Image Analysis	—Unverified
High-Resolution Boundary Detection for Medical Image Segmentation with Piece-Wise Two-Sample T-Test Augmented Loss	Nov 4, 2022	Boundary DetectionImage Segmentation	—Unverified
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation	Nov 3, 2022	Decision MakingImage Segmentation	—Unverified
Unsupervised Model Adaptation for Source-free Segmentation of Medical Images	Nov 2, 2022	Domain AdaptationImage Segmentation	—Unverified
Style Augmentation improves Medical Image Segmentation	Nov 2, 2022	Data AugmentationImage Segmentation	—Unverified
Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation	Nov 1, 2022	Image SegmentationMedical Image Segmentation	—Unverified
Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation	Oct 31, 2022	AttributeImage Segmentation	—Unverified
IB-U-Nets: Improving medical image segmentation tasks with 3D Inductive Biased kernels	Oct 28, 2022	Image SegmentationInductive Bias	CodeCode Available
FAS-UNet: A Novel FAS-driven Unet to Learn Variational Image Segmentation	Oct 27, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available
Accelerating Diffusion Models via Pre-segmentation Diffusion Sampling for Medical Image Segmentation	Oct 27, 2022	Conditional Image GenerationDenoising	—Unverified
UNet-2022: Exploring Dynamics in Non-isomorphic Architecture	Oct 27, 2022	Image SegmentationLesion Segmentation	—Unverified
Super-Resolution Based Patch-Free 3D Image Segmentation with High-Frequency Guidance	Oct 26, 2022	Computed Tomography (CT)GPU	CodeCode Available
How precise are performance estimates for typical medical image segmentation tasks?	Oct 26, 2022	Image SegmentationMedical Image Segmentation	—Unverified
IDEAL: Improved DEnse locAL Contrastive Learning for Semi-Supervised Medical Image Segmentation	Oct 26, 2022	Contrastive LearningImage 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