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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 1101–1150 of 2089 papers

TitleStatusHype
Improving Segment Anything on the Fly: Auxiliary Online Learning and Adaptive Fusion for Medical Image Segmentation—0
SimSAM: Zero-shot Medical Image Segmentation via Simulated InteractionCode0
CRIS: Collaborative Refinement Integrated with Segmentation for Polyp Segmentation—0
CBAR‑UNet: A novel methodology for segmentation of cardiac magnetic resonance images using block attention‑based deep residual neural networkCode0
FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms—0
Advancing Medical Image Segmentation with Mini-Net: A Lightweight Solution Tailored for Efficient Segmentation of Medical Images—0
FRCNet Frequency and Region Consistency for Semi-supervised Medical Image Segmentation—0
A Classifier-Free Incremental Learning Framework for Scalable Medical Image Segmentation—0
DuEDL: Dual-Branch Evidential Deep Learning for Scribble-Supervised Medical Image SegmentationCode0
A temporal enhanced semi-supervised segmentation network for needle detection in 3D ultrasound images—0
Hi-gMISnet: generalized medical image segmentation using DWT based multilayer fusion and dual mode attention into high resolution pGANCode0
Multi-dimension Transformer with Attention-based Filtering for Medical Image Segmentation—0
Blackbox Adaptation for Medical Image SegmentationCode0
Rethinking Barely-Supervised Volumetric Medical Image Segmentation from an Unsupervised Domain Adaptation PerspectiveCode0
CTS: A Consistency-Based Medical Image Segmentation ModelCode0
Towards Clinician-Preferred Segmentation: Leveraging Human-in-the-Loop for Test Time Adaptation in Medical Image Segmentation—0
Shape-aware synthesis of pathological lung CT scans using CycleGAN for enhanced semi-supervised lung segmentationCode0
Support-Query Prototype Fusion Network for Few-shot Medical Image Segmentation—0
Adaptation of Distinct Semantics for Uncertain Areas in Polyp SegmentationCode0
Leveraging Fixed and Dynamic Pseudo-labels for Semi-supervised Medical Image Segmentation—0
PCLMix: Weakly Supervised Medical Image Segmentation via Pixel-Level Contrastive Learning and Dynamic Mix AugmentationCode0
HC-Mamba: Vision MAMBA with Hybrid Convolutional Techniques for Medical Image Segmentation—0
Lumbar Spine Tumor Segmentation and Localization in T2 MRI Images Using AI—0
Implantable Adaptive Cells: differentiable architecture search to improve the performance of any trained U-shaped networkCode0
On Enhancing Brain Tumor Segmentation Across Diverse Populations with Convolutional Neural NetworksCode0
Predictive Accuracy-Based Active Learning for Medical Image SegmentationCode0
DmADs-Net: Dense multiscale attention and depth-supervised network for medical image segmentation—0
Rethinking Attention Gated with Hybrid Dual Pyramid Transformer-CNN for Generalized Segmentation in Medical ImagingCode0
GLIMS: Attention-Guided Lightweight Multi-Scale Hybrid Network for Volumetric Semantic SegmentationCode0
Segmentation Quality and Volumetric Accuracy in Medical Imaging—0
Discriminative features pyramid network for medical image segmentationCode0
Discriminative features pyramid network for medical image segmentationCode0
Semantic Segmentation Refiner for Ultrasound Applications with Zero-Shot Foundation Models—0
DiffSeg: A Segmentation Model for Skin Lesions Based on Diffusion Difference—0
Mitigating False Predictions In Unreasonable Body Regions—0
CFPFormer: Feature-pyramid like Transformer Decoder for Segmentation and Detection—0
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation—0
Beyond Pixel-Wise Supervision for Medical Image Segmentation: From Traditional Models to Foundation Models—0
ToNNO: Tomographic Reconstruction of a Neural Network's Output for Weakly Supervised Segmentation of 3D Medical Images—0
Cross-model Mutual Learning for Exemplar-based Medical Image Segmentation—0
Boosting Medical Image Segmentation Performance with Adaptive Convolution LayerCode0
Mixed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation—0
Q2A: Querying Implicit Fully Continuous Feature Pyramid to Align Features for Medical Image Segmentation—0
Post-Training Network Compression for 3D Medical Image Segmentation: Reducing Computational Efforts via Tucker DecompositionCode0
Multi-rater Prompting for Ambiguous Medical Image Segmentation—0
An Evidential-enhanced Tri-Branch Consistency Learning Method for Semi-supervised Medical Image Segmentation—0
Uncertainty-aware Evidential Fusion-based Learning for Semi-supervised Medical Image Segmentation—0
EPL: Evidential Prototype Learning for Semi-supervised Medical Image Segmentation—0
Towards Efficient and Accurate CT Segmentation via Edge-Preserving Probabilistic Downsampling—0
Adaptive Affinity-Based Generalization For MRI Imaging Segmentation Across Resource-Limited Settings—0
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All datasetsKvasir-SEGCVC-ClinicDBCVC-ColonDBETIS-LARIBPOLYPDBSynapse multi-organ CTAutomatic Cardiac Diagnosis Challenge (ACDC)MoNuSeg2018 Data Science BowlGlaSBKAI-IGH NeoPolyp-SmallMICCAI 2015 Multi-Atlas Abdomen Labeling ChallengeACDC

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