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 676–700 of 2089 papers

Title	Date	Tasks	Status	Hype
Test-Time Adaptable Neural Networks for Robust Medical Image Segmentation	Apr 9, 2020	DenoisingDomain Generalization	CodeCode Available	1
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks	Mar 28, 2020	3D Medical Imaging SegmentationAction Recognition	CodeCode Available	1
Multi-level Context Gating of Embedded Collective Knowledge for Medical Image Segmentation	Mar 10, 2020	AnatomyImage Segmentation	CodeCode Available	1
Automatic segmentation of spinal multiple sclerosis lesions: How to generalize across MRI contrasts?	Mar 9, 2020	Image SegmentationLesion Segmentation	CodeCode Available	1
Robust Multimodal Brain Tumor Segmentation via Feature Disentanglement and Gated Fusion	Feb 22, 2020	Brain Tumor SegmentationDisentanglement	CodeCode Available	1
Panoptic Feature Fusion Net: A Novel Instance Segmentation Paradigm for Biomedical and Biological Images	Feb 15, 2020	Instance SegmentationMedical Image Segmentation	CodeCode Available	1
Unsupervised Bidirectional Cross-Modality Adaptation via Deeply Synergistic Image and Feature Alignment for Medical Image Segmentation	Feb 6, 2020	Domain AdaptationImage Segmentation	CodeCode Available	1
Medical Image Segmentation via Unsupervised Convolutional Neural Network	Jan 28, 2020	Image SegmentationMedical Image Segmentation	CodeCode Available	1
RatLesNetv2: A Fully Convolutional Network for Rodent Brain Lesion Segmentation	Jan 24, 2020	Image SegmentationLesion Segmentation	CodeCode Available	1
SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentation	Jan 21, 2020	Image SegmentationMedical Image Segmentation	CodeCode Available	1
A context based deep learning approach for unbalanced medical image segmentation	Jan 8, 2020	Deep LearningImage Segmentation	CodeCode Available	1
UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation	Dec 11, 2019	Computed Tomography (CT)Decoder	CodeCode Available	1
ResUNet++: An Advanced Architecture for Medical Image Segmentation	Nov 16, 2019	Colorectal Polyps CharacterizationImage Segmentation	CodeCode Available	1
One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation	Nov 5, 2019	AllData Augmentation	CodeCode Available	1
3D U^2-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation	Sep 4, 2019	image-classificationImage Classification	CodeCode Available	1
Bi-Directional ConvLSTM U-Net with Densley Connected Convolutions	Aug 31, 2019	Image SegmentationLesion Segmentation	CodeCode Available	1
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis	Aug 19, 2019	AnatomyBrain Tumor Segmentation	CodeCode Available	1
Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation	Jul 16, 2019	Image SegmentationLeft Atrium Segmentation	CodeCode Available	1
A Partially Reversible U-Net for Memory-Efficient Volumetric Image Segmentation	Jun 14, 2019	image-classificationImage Classification	CodeCode Available	1
PHiSeg: Capturing Uncertainty in Medical Image Segmentation	Jun 7, 2019	Image SegmentationMedical Image Segmentation	CodeCode Available	1
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities	May 30, 2019	DiversityInductive Bias	CodeCode Available	1
Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation	Jan 24, 2019	Domain AdaptationImage Segmentation	CodeCode Available	1
Boundary loss for highly unbalanced segmentation	Dec 17, 2018	Brain Lesion Segmentation From MriIschemic Stroke Lesion Segmentation	CodeCode Available	1
nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation	Sep 27, 2018	Image SegmentationMedical Image Segmentation	CodeCode Available	1
UNet++: A Nested U-Net Architecture for Medical Image Segmentation	Jul 18, 2018	Camouflaged Object SegmentationImage Segmentation	CodeCode Available	1

Show:10 25 50

← PrevPage 28 of 84Next →

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