SOTAVerified

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

Showing 151–200 of 2089 papers

TitleStatusHype
SALT: Singular Value Adaptation with Low-Rank TransformationCode1
Multi-Prototype Embedding Refinement for Semi-Supervised Medical Image SegmentationCode1
GBT-SAM: Adapting a Foundational Deep Learning Model for Generalizable Brain Tumor Segmentation via Efficient Integration of Multi-Parametric MRI DataCode1
WeakMedSAM: Weakly-Supervised Medical Image Segmentation via SAM with Sub-Class Exploration and Prompt Affinity MiningCode1
Federated nnU-Net for Privacy-Preserving Medical Image SegmentationCode1
From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image SegmentationCode1
VesselSAM: Leveraging SAM for Aortic Vessel Segmentation with AtrousLoRACode1
Leveraging Labelled Data Knowledge: A Cooperative Rectification Learning Network for Semi-supervised 3D Medical Image SegmentationCode1
QMaxViT-Unet+: A Query-Based MaxViT-Unet with Edge Enhancement for Scribble-Supervised Segmentation of Medical ImagesCode1
Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentationCode1
Conditional diffusion model with spatial attention and latent embedding for medical image segmentationCode1
UD-Mamba: A pixel-level uncertainty-driven Mamba model for medical image segmentationCode1
SeqSeg: Learning Local Segments for Automatic Vascular Model ConstructionCode1
MedicoSAM: Towards foundation models for medical image segmentationCode1
LM-Net: A Light-weight and Multi-scale Network for Medical Image SegmentationCode1
AIF-SFDA: Autonomous Information Filter-driven Source-Free Domain Adaptation for Medical Image SegmentationCode1
KM-UNet KAN Mamba UNet for medical image segmentationCode1
EffiDec3D: An Optimized Decoder for High-Performance and Efficient 3D Medical Image SegmentationCode1
Modality-Projection Universal Model for Comprehensive Full-Body Medical Imaging SegmentationCode1
QTSeg: A Query Token-Based Architecture for Efficient 2D Medical Image SegmentationCode1
DuSSS: Dual Semantic Similarity-Supervised Vision-Language Model for Semi-Supervised Medical Image SegmentationCode1
MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One DayCode1
MRGen: Diffusion-based Controllable Data Engine for MRI Segmentation towards Unannotated ModalitiesCode1
A SAM-guided and Match-based Semi-Supervised Segmentation Framework for Medical ImagingCode1
MulModSeg: Enhancing Unpaired Multi-Modal Medical Image Segmentation with Modality-Conditioned Text Embedding and Alternating TrainingCode1
MLLA-UNet: Mamba-like Linear Attention in an Efficient U-Shape Model for Medical Image SegmentationCode1
Gaze-Assisted Medical Image SegmentationCode1
EViT-Unet: U-Net Like Efficient Vision Transformer for Medical Image Segmentation on Mobile and Edge DevicesCode1
Shape Transformation Driven by Active Contour for Class-Imbalanced Semi-Supervised Medical Image SegmentationCode1
STA-Unet: Rethink the semantic redundant for Medical Imaging SegmentationCode1
UnSeGArmaNet: Unsupervised Image Segmentation using Graph Neural Networks with Convolutional ARMA FiltersCode1
DB-SAM: Delving into High Quality Universal Medical Image SegmentationCode1
Med-TTT: Vision Test-Time Training model for Medical Image SegmentationCode1
PASS:Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image SegmentationCode1
TransResNet: Integrating the Strengths of ViTs and CNNs for High Resolution Medical Image Segmentation via Feature GraftingCode1
SDCL: Students Discrepancy-Informed Correction Learning for Semi-supervised Medical Image SegmentationCode1
MambaClinix: Hierarchical Gated Convolution and Mamba-Based U-Net for Enhanced 3D Medical Image SegmentationCode1
Prompting Segment Anything Model with Domain-Adaptive Prototype for Generalizable Medical Image SegmentationCode1
MetaFormer and CNN Hybrid Model for Polyp Image SegmentationCode1
Do Vision Foundation Models Enhance Domain Generalization in Medical Image Segmentation?Code1
Swin-LiteMedSAM: A Lightweight Box-Based Segment Anything Model for Large-Scale Medical Image DatasetsCode1
Sam2Rad: A Segmentation Model for Medical Images with Learnable PromptsCode1
Structure-Aware Single-Source Generalization with Pixel-Level Disentanglement for Joint Optic Disc and Cup SegmentationCode1
PMT: Progressive Mean Teacher via Exploring Temporal Consistency for Semi-Supervised Medical Image SegmentationCode1
Labeled-to-Unlabeled Distribution Alignment for Partially-Supervised Multi-Organ Medical Image SegmentationCode1
SMAFormer: Synergistic Multi-Attention Transformer for Medical Image SegmentationCode1
A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentationCode1
LV-UNet: A Lightweight and Vanilla Model for Medical Image SegmentationCode1
LoG-VMamba: Local-Global Vision Mamba for Medical Image SegmentationCode1
SAM-UNet:Enhancing Zero-Shot Segmentation of SAM for Universal Medical ImagesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DUCK-Netmean Dice0.95—Unverified
2EffiSegNet-B5mean Dice0.95—Unverified
3EffiSegNet-B4mean Dice0.95—Unverified
4SegMedmean Dice0.95—Unverified
5FCB Formermean Dice0.94—Unverified
6FCB-SwinV2 Transformermean Dice0.94—Unverified
7SEPmean Dice0.94—Unverified
8LM-Netmean Dice0.94—Unverified
9RAPUNetmean Dice0.94—Unverified
10FCBFormermean Dice0.94—Unverified
#ModelMetricClaimedVerifiedStatus
1DUCK-Netmean Dice0.97—Unverified
2RAPUNetmean Dice0.96—Unverified
3EMCADmean Dice0.95—Unverified
4Yolo-SAM 2mean Dice0.95—Unverified
5RaBiTmean Dice0.95—Unverified
6UGCANetmean Dice0.95—Unverified
7ESFPNet-Lmean Dice0.95—Unverified
8FCBFormermean Dice0.95—Unverified
9SegMedmean Dice0.95—Unverified
10DuATmean Dice0.95—Unverified
#ModelMetricClaimedVerifiedStatus
1RAPUNetmean Dice0.95—Unverified
2DUCK-Netmean Dice0.94—Unverified
3EMCADmean Dice0.92—Unverified
4SegMedmean Dice0.92—Unverified
5UniNetmean Dice0.92—Unverified
6ProMISemean Dice0.87—Unverified
7Meta-Polypmean Dice0.87—Unverified
8ResUNet++ + TTAmean Dice0.85—Unverified
9PVT-GCASCADEmean Dice0.83—Unverified
10PVT-CASCADEmean Dice0.83—Unverified
#ModelMetricClaimedVerifiedStatus
1RAPUNetmean Dice0.96—Unverified
2SegMedmean Dice0.94—Unverified
3DUCK-Netmean Dice0.94—Unverified
4EMCADmean Dice0.92—Unverified
5ProMISemean Dice0.84—Unverified
6RSAFormermean Dice0.84—Unverified
7ESFPNet-Lmean Dice0.82—Unverified
8DuATmean Dice0.82—Unverified
9PVT-CASCADEmean Dice0.8—Unverified
10SSFormer-Lmean Dice0.8—Unverified
#ModelMetricClaimedVerifiedStatus
1Interactive AI-SAM gt boxAvg DSC90.66—Unverified
2Medical SAM AdapterAvg DSC89.8—Unverified
3MedSegDiff-v2Avg DSC89.5—Unverified
4nnUNetAvg DSC88.8—Unverified
5MedNeXt-L (5x5x5)Avg DSC88.76—Unverified
6MISTAvg DSC86.92—Unverified
7nnFormerAvg DSC86.57—Unverified
8AgileFormerAvg DSC86.11—Unverified
9MERITAvg DSC84.9—Unverified
10Automatic AI-SAMAvg DSC84.21—Unverified
#ModelMetricClaimedVerifiedStatus
1FCTAvg DSC94.26—Unverified
2Interactive AI-SAM gt boxAvg DSC93.89—Unverified
3FCTAvg DSC93.02—Unverified
4LHU-NetAvg DSC92.65—Unverified
5MISTAvg DSC92.56—Unverified
6MERITAvg DSC92.32—Unverified
7MERIT-GCASCADEAvg DSC92.23—Unverified
8EMCADAvg DSC92.12—Unverified
9Automatic AI-SAMAvg DSC92.06—Unverified
10nnFormerAvg DSC92.06—Unverified
#ModelMetricClaimedVerifiedStatus
1StardistF184.6—Unverified