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 576–600 of 2089 papers

Title	Date	Tasks	Status	Hype
DmADs-Net: Dense multiscale attention and depth-supervised network for medical image segmentation	May 1, 2024	Image SegmentationMedical Image Segmentation	—Unverified	0
Adaptive Bidirectional Displacement for Semi-Supervised Medical Image Segmentation	May 1, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	2
A Flexible 2.5D Medical Image Segmentation Approach with In-Slice and Cross-Slice Attention	Apr 30, 2024	Computational EfficiencyImage Segmentation	CodeCode Available	1
Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical Imaging	Apr 28, 2024	Medical Image SegmentationSegmentation	CodeCode Available	0
Segmentation Quality and Volumetric Accuracy in Medical Imaging	Apr 27, 2024	Image SegmentationMedical Image Segmentation	—Unverified	0
GLIMS: Attention-Guided Lightweight Multi-Scale Hybrid Network for Volumetric Semantic Segmentation	Apr 27, 2024	BraTS2021Image Segmentation	CodeCode Available	0
Discriminative features pyramid network for medical image segmentation	Apr 25, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	0
Discriminative features pyramid network for medical image segmentation	Apr 25, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	0
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
Multimodal Information Interaction for Medical Image Segmentation	Apr 25, 2024	Heart SegmentationImage Segmentation	CodeCode Available	2
Semantic Segmentation Refiner for Ultrasound Applications with Zero-Shot Foundation Models	Apr 25, 2024	Image SegmentationMedical Image Segmentation	—Unverified	0
DiffSeg: A Segmentation Model for Skin Lesions Based on Diffusion Difference	Apr 25, 2024	Decision MakingImage Segmentation	—Unverified	0
Mitigating False Predictions In Unreasonable Body Regions	Apr 24, 2024	Domain GeneralizationImage Segmentation	—Unverified	0
CFPFormer: Feature-pyramid like Transformer Decoder for Segmentation and Detection	Apr 23, 2024	DecoderImage Segmentation	—Unverified	0
Ultrasound SAM Adapter: Adapting SAM for Breast Lesion Segmentation in Ultrasound Images	Apr 23, 2024	Image SegmentationLesion Segmentation	CodeCode Available	1
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation	Apr 21, 2024	Computed Tomography (CT)Image Segmentation	—Unverified	0
Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models	Apr 20, 2024	Image SegmentationMedical Image Segmentation	—Unverified	0
ToNNO: Tomographic Reconstruction of a Neural Network's Output for Weakly Supervised Segmentation of 3D Medical Images	Apr 19, 2024	Image SegmentationMedical Image Segmentation	—Unverified	0
Cross-model Mutual Learning for Exemplar-based Medical Image Segmentation	Apr 18, 2024	Image SegmentationMedical Image Segmentation	—Unverified	0
Boosting Medical Image Segmentation Performance with Adaptive Convolution Layer	Apr 17, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available	0
Mixed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation	Apr 16, 2024	Image SegmentationMedical Image Segmentation	—Unverified	0
How to build the best medical image segmentation algorithm using foundation models: a comprehensive empirical study with Segment Anything Model	Apr 15, 2024	DecoderImage Segmentation	CodeCode Available	3
SegFormer3D: an Efficient Transformer for 3D Medical Image Segmentation	Apr 15, 2024	Brain Tumor SegmentationDecoder	CodeCode Available	3
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker Decomposition	Apr 15, 2024	Computational EfficiencyGPU	CodeCode Available	0
nnU-Net Revisited: A Call for Rigorous Validation in 3D Medical Image Segmentation	Apr 15, 2024	BenchmarkingImage Segmentation	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