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 201–225 of 2089 papers

Title	Date	Tasks	Status	Hype
Medical Semantic Segmentation with Diffusion Pretrain	Jan 31, 2025	Image SegmentationLinear evaluation	—Unverified	0
Post-Training Quantization for 3D Medical Image Segmentation: A Practical Study on Real Inference Engines	Jan 28, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available	0
Efficient Knowledge Distillation of SAM for Medical Image Segmentation	Jan 28, 2025	Computational EfficiencyDecoder	—Unverified	0
Point Cloud Upsampling as Statistical Shape Model for Pelvic	Jan 28, 2025	Image SegmentationMedical Image Analysis	—Unverified	0
LSU-Net: Lightweight Automatic Organs Segmentation Network For Medical Images	Jan 27, 2025	Image SegmentationMedical Image Segmentation	—Unverified	0
SeqSeg: Learning Local Segments for Automatic Vascular Model Construction	Jan 27, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available	1
ENSeg: A Novel Dataset and Method for the Segmentation of Enteric Neuron Cells on Microscopy Images	Jan 21, 2025	Instance SegmentationMedical Image Segmentation	CodeCode Available	0
A generalizable 3D framework and model for self-supervised learning in medical imaging	Jan 20, 2025	Medical Image SegmentationSelf-Supervised Learning	CodeCode Available	2
MedicoSAM: Towards foundation models for medical image segmentation	Jan 20, 2025	Image SegmentationInteractive Segmentation	CodeCode Available	1
Enhancing Brain Tumor Segmentation Using Channel Attention and Transfer learning	Jan 19, 2025	Brain Tumor SegmentationImage Segmentation	CodeCode Available	0
No More Sliding Window: Efficient 3D Medical Image Segmentation with Differentiable Top-k Patch Sampling	Jan 18, 2025	CPUGPU	—Unverified	0
Deep Distance Map Regression Network with Shape-aware Loss for Imbalanced Medical Image Segmentation	Jan 15, 2025	Image SegmentationMedical Image Analysis	—Unverified	0
Few-Shot Adaptation of Training-Free Foundation Model for 3D Medical Image Segmentation	Jan 15, 2025	Image SegmentationMedical Image Segmentation	—Unverified	0
RWKV-UNet: Improving UNet with Long-Range Cooperation for Effective Medical Image Segmentation	Jan 14, 2025	Computational EfficiencyImage Segmentation	CodeCode Available	2
FedSemiDG: Domain Generalized Federated Semi-supervised Medical Image Segmentation	Jan 13, 2025	Domain GeneralizationImage Segmentation	—Unverified	0
UNetVL: Enhancing 3D Medical Image Segmentation with Chebyshev KAN Powered Vision-LSTM	Jan 13, 2025	Computational EfficiencyImage Segmentation	CodeCode Available	0
PGP-SAM: Prototype-Guided Prompt Learning for Efficient Few-Shot Medical Image Segmentation	Jan 12, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available	0
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels	Jan 12, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available	0
Rethinking domain generalization in medical image segmentation: One image as one domain	Jan 8, 2025	DisentanglementDomain Generalization	—Unverified	0
LM-Net: A Light-weight and Multi-scale Network for Medical Image Segmentation	Jan 7, 2025	Image SegmentationMedical Image Segmentation	CodeCode Available	1
CFFormer: Cross CNN-Transformer Channel Attention and Spatial Feature Fusion for Improved Segmentation of Low Quality Medical Images	Jan 7, 2025	Image SegmentationMedical Image Segmentation	—Unverified	0
AIF-SFDA: Autonomous Information Filter-driven Source-Free Domain Adaptation for Medical Image Segmentation	Jan 6, 2025	Domain AdaptationImage Segmentation	CodeCode Available	1
GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation	Jan 6, 2025	Cardiac SegmentationImage Segmentation	CodeCode Available	0
PARF-Net: integrating pixel-wise adaptive receptive fields into hybrid Transformer-CNN network for medical image segmentation	Jan 6, 2025	Image SegmentationMedical Image Segmentation	—Unverified	0
MedSegDiffNCA: Diffusion Models With Neural Cellular Automata for Skin Lesion Segmentation	Jan 5, 2025	DenoisingImage Generation	—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	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