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 1751–1775 of 2089 papers

Title	Date	Tasks	Status
Atrous Residual Interconnected Encoder to Attention Decoder Framework for Vertebrae Segmentation via 3D Volumetric CT Images	Apr 8, 2021	Computed Tomography (CT)Decoder	—Unverified
BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation	Apr 8, 2021	DecoderDenoising	—Unverified
Global Guidance Network for Breast Lesion Segmentation in Ultrasound Images	Apr 5, 2021	Boundary DetectionImage Segmentation	—Unverified
Cascaded Robust Learning at Imperfect Labels for Chest X-ray Segmentation	Apr 5, 2021	Image SegmentationMedical Image Analysis	—Unverified
DARCNN: Domain Adaptive Region-based Convolutional Neural Network for Unsupervised Instance Segmentation in Biomedical Images	Apr 3, 2021	Domain AdaptationInstance Segmentation	CodeCode Available
DARCNN: Domain Adaptive Region-based Convolutional Neural Network forUnsupervised Instance Segmentation in Biomedical Images	Apr 3, 2021	Instance SegmentationMedical Image Segmentation	CodeCode Available
Deep ensembles based on Stochastic Activation Selection for Polyp Segmentation	Apr 2, 2021	Autonomous DrivingDecoder	—Unverified
Assessing the Role of Random Forests in Medical Image Segmentation	Mar 30, 2021	GPUImage Segmentation	—Unverified
DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation	Mar 29, 2021	GPUImage Segmentation	CodeCode Available
Catalyzing Clinical Diagnostic Pipelines Through Volumetric Medical Image Segmentation Using Deep Neural Networks: Past, Present, & Future	Mar 27, 2021	Deep LearningDiagnostic	—Unverified
Contextual Information Enhanced Convolutional Neural Networks for Retinal Vessel Segmentation in Color Fundus Images	Mar 25, 2021	DecoderImage Segmentation	—Unverified
Roughness Index and Roughness Distance for Benchmarking Medical Segmentation	Mar 23, 2021	BenchmarkingImage Segmentation	CodeCode Available
Spatially Dependent U-Nets: Highly Accurate Architectures for Medical Imaging Segmentation	Mar 22, 2021	Image SegmentationInductive Bias	—Unverified
Deep Label Fusion: A 3D End-to-End Hybrid Multi-Atlas Segmentation and Deep Learning Pipeline	Mar 19, 2021	Image SegmentationMedical Image Segmentation	—Unverified
Invertible Residual Network with Regularization for Effective Medical Image Segmentation	Mar 16, 2021	Image SegmentationMedical Image Segmentation	—Unverified
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient	Mar 10, 2021	Image SegmentationMedical Image Segmentation	—Unverified
Morphological Operation Residual Blocks: Enhancing 3D Morphological Feature Representation in Convolutional Neural Networks for Semantic Segmentation of Medical Images	Mar 6, 2021	Deep LearningImage Segmentation	—Unverified
Learning With Context Feedback Loop for Robust Medical Image Segmentation	Mar 4, 2021	Deep LearningImage Segmentation	CodeCode Available
Uncertainty guided semi-supervised segmentation of retinal layers in OCT images	Mar 2, 2021	Image SegmentationMedical Image Segmentation	—Unverified
Medical Image Segmentation with Limited Supervision: A Review of Deep Network Models	Feb 28, 2021	Deep LearningImage Segmentation	—Unverified
Convolution-Free Medical Image Segmentation using Transformers	Feb 26, 2021	Image SegmentationInductive Bias	—Unverified
A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution	Feb 19, 2021	DecoderDimensionality Reduction	—Unverified
Membership Inference Attacks are Easier on Difficult Problems	Feb 15, 2021	Image SegmentationMedical Image Segmentation	CodeCode Available
L-SNet: from Region Localization to Scale Invariant Medical Image Segmentation	Feb 11, 2021	Image SegmentationMedical Image Segmentation	—Unverified
A Systematic Approach for MRI Brain Tumor Localization, and Segmentation using Deep Learning and Active Contouring	Feb 6, 2021	Edge DetectionImage 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