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 1051–1075 of 2089 papers

Title	Date	Tasks	Status	Hype
STM-UNet: An Efficient U-shaped Architecture Based on Swin Transformer and Multi-scale MLP for Medical Image Segmentation	Apr 25, 2023	Image SegmentationMedical Image Segmentation	—Unverified	0
Generalist Vision Foundation Models for Medical Imaging: A Case Study of Segment Anything Model on Zero-Shot Medical Segmentation	Apr 25, 2023	Computed Tomography (CT)Image Segmentation	CodeCode Available	1
Segment Anything in Medical Images	Apr 24, 2023	DiagnosticImage Segmentation	CodeCode Available	4
Dilated-UNet: A Fast and Accurate Medical Image Segmentation Approach using a Dilated Transformer and U-Net Architecture	Apr 22, 2023	DecoderDiagnostic	CodeCode Available	0
Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model	Apr 22, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation	Apr 21, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Segment Anything Model for Medical Image Analysis: an Experimental Study	Apr 20, 2023	Image SegmentationInteractive Segmentation	CodeCode Available	1
Few-shot Medical Image Segmentation via Cross-Reference Transformer	Apr 19, 2023	Few-Shot LearningImage Segmentation	—Unverified	0
SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More	Apr 18, 2023	General KnowledgeImage Segmentation	CodeCode Available	3
Computer-Vision Benchmark Segment-Anything Model (SAM) in Medical Images: Accuracy in 12 Datasets	Apr 18, 2023	Image SegmentationMedical Image Segmentation	—Unverified	0
When SAM Meets Medical Images: An Investigation of Segment Anything Model (SAM) on Multi-phase Liver Tumor Segmentation	Apr 17, 2023	Image SegmentationMedical Image Analysis	—Unverified	0
Compete to Win: Enhancing Pseudo Labels for Barely-supervised Medical Image Segmentation	Apr 15, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
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	0
UniverSeg: Universal Medical Image Segmentation	Apr 12, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	2
Automated computed tomography and magnetic resonance imaging segmentation using deep learning: a beginner's guide	Apr 12, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Scale-Equivariant Deep Learning for 3D Data	Apr 12, 2023	Deep LearningImage Segmentation	CodeCode Available	0
Unifying and Personalizing Weakly-supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation	Apr 12, 2023	channel selectionFederated Learning	CodeCode Available	2
Weakly Supervised Intracranial Hemorrhage Segmentation using Head-Wise Gradient-Infused Self-Attention Maps from a Swin Transformer in Categorical Learning	Apr 11, 2023	Binary ClassificationImage Segmentation	CodeCode Available	0
SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model	Apr 10, 2023	Image GenerationImage Segmentation	—Unverified	0
Self-training with dual uncertainty for semi-supervised medical image segmentation	Apr 10, 2023	Image SegmentationMedical Image Segmentation	—Unverified	0
Ambiguous Medical Image Segmentation using Diffusion Models	Apr 10, 2023	DiagnosticDiversity	CodeCode Available	2
HST-MRF: Heterogeneous Swin Transformer with Multi-Receptive Field for Medical Image Segmentation	Apr 10, 2023	Image SegmentationLesion Segmentation	—Unverified	0
BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation	Apr 10, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Transformer Utilization in Medical Image Segmentation Networks	Apr 9, 2023	Image SegmentationMedical Image Segmentation	—Unverified	0
MedGen3D: A Deep Generative Framework for Paired 3D Image and Mask Generation	Apr 8, 2023	Image SegmentationMedical Image Segmentation	—Unverified	0

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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	SegMed	mean Dice	0.95	—	Unverified
10	DuAT	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	Automatic AI-SAM	Avg DSC	92.06	—	Unverified
10	nnFormer	Avg DSC	92.06	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Stardist	F1	84.6	—	Unverified