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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 1351–1400 of 2089 papers

TitleStatusHype
Optimal Surface Segmentation with Convex Priors in Irregularly Sampled Space—0
Optimization for Medical Image Segmentation: Theory and Practice when evaluating with Dice Score or Jaccard Index—0
Optimization of MedSAM model based on bounding box adaptive perturbation algorithm—0
Organ-aware Multi-scale Medical Image Segmentation Using Text Prompt Engineering—0
Organ Segmentation From Full-size CT Images Using Memory-Efficient FCN—0
P3Net: Progressive and Periodic Perturbation for Semi-Supervised Medical Image Segmentation—0
PAANet: Progressive Alternating Attention for Automatic Medical Image Segmentation—0
PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation—0
PAN: Projective Adversarial Network for Medical Image Segmentation—0
Parameter-Efficient Transformer with Hybrid Axial-Attention for Medical Image Segmentation—0
PARF-Net: integrating pixel-wise adaptive receptive fields into hybrid Transformer-CNN network for medical image segmentation—0
Partially Supervised Unpaired Multi-Modal Learning for Label-Efficient Medical Image Segmentation—0
Partly Supervised Multitask Learning—0
Patch-based Medical Image Segmentation using Matrix Product State Tensor Networks—0
Patch Network for medical image Segmentation—0
Pathological Retinal Region Segmentation From OCT Images Using Geometric Relation Based Augmentation—0
Pay Attention to the Atlas: Atlas-Guided Test-Time Adaptation Method for Robust 3D Medical Image Segmentation—0
PCA for Enhanced Cross-Dataset Generalizability in Breast Ultrasound Tumor Segmentation—0
PCA: Semi-supervised Segmentation with Patch Confidence Adversarial Training—0
PCCA-Model: an attention module for medical image segmentation—0
PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation—0
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation—0
Penalizing small errors using an Adaptive Logarithmic Loss—0
Performance Analysis of Deep Learning Models for Femur Segmentation in MRI Scan—0
Performance Analysis of UNet and Variants for Medical Image Segmentation—0
Performance Estimation for Supervised Medical Image Segmentation Models on Unlabeled Data Using UniverSeg—0
pFLFE: Cross-silo Personalized Federated Learning via Feature Enhancement on Medical Image Segmentation—0
PGDiffSeg: Prior-Guided Denoising Diffusion Model with Parameter-Shared Attention for Breast Cancer Segmentation—0
PGD-UNet: A Position-Guided Deformable Network for Simultaneous Segmentation of Organs and Tumors—0
PGL: Prior-Guided Local Self-supervised Learning for 3D Medical Image Segmentation—0
Phase Collaborative Network for Two-Phase Medical Image Segmentation—0
PICS in Pics: Physics Informed Contour Selection for Rapid Image Segmentation—0
PINN-EMFNet: PINN-based and Enhanced Multi-Scale Feature Fusion Network for Breast Ultrasound Images Segmentation—0
Pitfalls of topology-aware image segmentation—0
Pixel-wise Modulated Dice Loss for Medical Image Segmentation—0
PL-Net: Progressive Learning Network for Medical Image Segmentation—0
PLU-Net: Extraction of multi-scale feature fusion—0
PlutoNet: An Efficient Polyp Segmentation Network with Modified Partial Decoder and Decoder Consistency Training—0
PMR-Net: Parallel Multi-Resolution Encoder-Decoder Network Framework for Medical Image Segmentation—0
Point Cloud Upsampling as Statistical Shape Model for Pelvic—0
PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation via Poisson Learning—0
PRAD: Periapical Radiograph Analysis Dataset and Benchmark Model Development—0
Predicting Scores of Medical Imaging Segmentation Methods with Meta-Learning—0
Primus: Enforcing Attention Usage for 3D Medical Image Segmentation—0
Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation—0
Probabilistic Modeling of Inter- and Intra-observer Variability in Medical Image Segmentation—0
Progressive Adversarial Semantic Segmentation—0
ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation—0
ProMamba: Prompt-Mamba for polyp segmentation—0
Prompt-Based Tuning of Transformer Models for Multi-Center Medical Image Segmentation of Head and Neck Cancer—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
9DuATmean Dice0.95—Unverified
10SegMedmean 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
9nnFormerAvg DSC92.06—Unverified
10Automatic AI-SAMAvg DSC92.06—Unverified
#ModelMetricClaimedVerifiedStatus
1StardistF184.6—Unverified