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 151–175 of 2089 papers

Title	Date	Tasks	Status	Hype
AIF-SFDA: Autonomous Information Filter-driven Source-Free Domain Adaptation for Medical Image Segmentation	Jan 6, 2025	Domain AdaptationImage Segmentation	CodeCode Available	1
Auto-Generating Weak Labels for Real & Synthetic Data to Improve Label-Scarce Medical Image Segmentation	Apr 25, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Interactive 3D Medical Image Segmentation with SAM 2	Aug 5, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	1
Annotation-efficient deep learning for automatic medical image segmentation	Dec 9, 2020	Deep LearningImage Segmentation	CodeCode Available	1
Attention U-Net: Learning Where to Look for the Pancreas	Apr 11, 2018	Brain Tumor SegmentationComputational Efficiency	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
Densely Connected Convolutional Networks	Aug 25, 2016	Breast Tumour ClassificationClassification	CodeCode Available	1
DB-SAM: Delving into High Quality Universal Medical Image Segmentation	Oct 5, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	1
DA-TransUNet: Integrating Spatial and Channel Dual Attention with Transformer U-Net for Medical Image Segmentation	Oct 19, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation	Feb 2, 2022	DecoderImage Segmentation	CodeCode Available	1
CycleMix: A Holistic Strategy for Medical Image Segmentation from Scribble Supervision	Mar 3, 2022	Image SegmentationMedical Image Segmentation	CodeCode Available	1
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentation	Aug 29, 2024	Image SegmentationLesion Segmentation	CodeCode Available	1
DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation	Dec 27, 2022	Image SegmentationLesion Segmentation	CodeCode Available	1
DC-UNet: Rethinking the U-Net Architecture with Dual Channel Efficient CNN for Medical Images Segmentation	May 31, 2020	DecoderImage Segmentation	CodeCode Available	1
CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation	Sep 23, 2022	Contrastive LearningImage Segmentation	CodeCode Available	1
CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image Segmentation	Nov 8, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
CSWin-UNet: Transformer UNet with Cross-Shaped Windows for Medical Image Segmentation	Jul 25, 2024	Computational EfficiencyDecoder	CodeCode Available	1
Cutting-edge 3D Medical Image Segmentation Methods in 2020: Are Happy Families All Alike?	Jan 1, 2021	AllImage Segmentation	CodeCode Available	1
DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation	Dec 30, 2020	Colorectal Polyps CharacterizationDecision Making	CodeCode Available	1
Cross-Modal Conditioned Reconstruction for Language-guided Medical Image Segmentation	Apr 3, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	1
ACC-UNet: A Completely Convolutional UNet model for the 2020s	Aug 25, 2023	Image SegmentationMedical Image Segmentation	CodeCode Available	1
CrossMatch: Enhance Semi-Supervised Medical Image Segmentation with Perturbation Strategies and Knowledge Distillation	May 1, 2024	Image SegmentationKnowledge Distillation	CodeCode Available	1
3DConvCaps: 3DUnet with Convolutional Capsule Encoder for Medical Image Segmentation	May 19, 2022	DecoderHippocampus	CodeCode Available	1
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation	Jan 8, 2022	Brain SegmentationDomain Adaptation	CodeCode Available	1
Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label Fusion	Feb 4, 2022	Computational EfficiencyImage Registration	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	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