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 1176–1200 of 2089 papers

Title	Date	Tasks	Status
Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation	Mar 11, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available
A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset	Mar 11, 2024	Binary ClassificationClassification	—Unverified
Shortcut Learning in Medical Image Segmentation	Mar 11, 2024	image-classificationImage Classification	CodeCode Available
Self and Mixed Supervision to Improve Training Labels for Multi-Class Medical Image Segmentation	Mar 6, 2024	Image SegmentationMedical Image Segmentation	—Unverified
Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications to Cardiac MRI Segmentation	Mar 4, 2024	Data AugmentationImage Segmentation	—Unverified
GLFNET: Global-Local (frequency) Filter Networks for efficient medical image segmentation	Mar 1, 2024	Image SegmentationMedical Image Segmentation	—Unverified
Efficient 3D affinely equivariant CNNs with adaptive fusion of augmented spherical Fourier-Bessel bases	Feb 26, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available
Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image Segmentation	Feb 22, 2024	Contrastive LearningImage Segmentation	CodeCode Available
FESS Loss: Feature-Enhanced Spatial Segmentation Loss for Optimizing Medical Image Analysis	Feb 13, 2024	Contrastive LearningImage Segmentation	CodeCode Available
Two-Stage Multi-task Self-Supervised Learning for Medical Image Segmentation	Feb 11, 2024	Auxiliary LearningImage Segmentation	—Unverified
Expert-Adaptive Medical Image Segmentation	Feb 11, 2024	Brain SegmentationImage Segmentation	—Unverified
An Optimization Framework for Processing and Transfer Learning for the Brain Tumor Segmentation	Feb 10, 2024	Brain Tumor SegmentationImage Segmentation	CodeCode Available
Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domain	Feb 9, 2024	Contrastive LearningImage Segmentation	—Unverified
Architecture Analysis and Benchmarking of 3D U-shaped Deep Learning Models for Thoracic Anatomical Segmentation	Feb 5, 2024	BenchmarkingImage Segmentation	CodeCode Available
Constrained Multiview Representation for Self-supervised Contrastive Learning	Feb 5, 2024	Contrastive LearningDisentanglement	—Unverified
Densely Decoded Networks with Adaptive Deep Supervision for Medical Image Segmentation	Feb 5, 2024	DecoderImage Segmentation	—Unverified
SPCTNet: A Series-Parallel CNN and Transformer Network for 3D Medical Image Segmentation	Feb 4, 2024	Image SegmentationMedical Image Segmentation	—Unverified
Exploring Intrinsic Properties of Medical Images for Self-Supervised Binary Semantic Segmentation	Feb 4, 2024	DecoderImage Segmentation	—Unverified
VIS-MAE: An Efficient Self-supervised Learning Approach on Medical Image Segmentation and Classification	Feb 1, 2024	Image SegmentationMedical Image Segmentation	CodeCode Available
Analog In-Memory Computing with Uncertainty Quantification for Efficient Edge-based Medical Imaging Segmentation	Feb 1, 2024	Medical Image SegmentationUncertainty Quantification	—Unverified
Breaking the Barrier: Selective Uncertainty-based Active Learning for Medical Image Segmentation	Jan 29, 2024	Active LearningImage Segmentation	CodeCode Available
MOSformer: Momentum encoder-based inter-slice fusion transformer for medical image segmentation	Jan 22, 2024	Computational EfficiencyImage Segmentation	—Unverified
Susceptibility of Adversarial Attack on Medical Image Segmentation Models	Jan 20, 2024	Adversarial AttackImage Segmentation	CodeCode Available
Artificial Intelligence-based algorithms in medical image scan seg-mentation and intelligent visual-content generation -- a concise overview	Jan 18, 2024	Image SegmentationMedical Image Segmentation	—Unverified
Harmonized Spatial and Spectral Learning for Robust and Generalized Medical Image Segmentation	Jan 18, 2024	Cardiac SegmentationImage 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