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 1151–1200 of 2089 papers

TitleStatusHype
Teaching AI the Anatomy Behind the Scan: Addressing Anatomical Flaws in Medical Image Segmentation with Learnable Prior—0
AI-Driven MRI-based Brain Tumour Segmentation Benchmarking—0
AI in the Loop -- Functionalizing Fold Performance Disagreement to Monitor Automated Medical Image Segmentation Pipelines—0
Airway Tree Modeling Using Dual-channel 3D UNet 3+ with Vesselness Prior—0
A Latent Source Model for Patch-Based Image Segmentation—0
Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks—0
All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation—0
AMLP:Adaptive Masking Lesion Patches for Self-supervised Medical Image Segmentation—0
Analog In-Memory Computing with Uncertainty Quantification for Efficient Edge-based Medical Imaging Segmentation—0
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation—0
Analysis of Vision-based Abnormal Red Blood Cell Classification—0
An Attentive Representative Sample Selection Strategy Combined with Balanced Batch Training for Skin Lesion Segmentation—0
An Efficient Multi-Scale Fusion Network for 3D Organ at Risk (OAR) Segmentation—0
An Empirical Study on the Fairness of Foundation Models for Multi-Organ Image Segmentation—0
An Ensemble Approach for Brain Tumor Segmentation and Synthesis—0
An evaluation of U-Net in Renal Structure Segmentation—0
An Evidential-enhanced Tri-Branch Consistency Learning Method for Semi-supervised Medical Image Segmentation—0
A new Level-set based Protocol for Accurate Bone Segmentation from CT Imaging—0
A New Validity Index for Fuzzy-Possibilistic C-Means Clustering—0
An Interactive Medical Image Segmentation Framework Using Iterative Refinement—0
Annotation Ambiguity Aware Semi-Supervised Medical Image Segmentation—0
Annotation by Clicks: A Point-Supervised Contrastive Variance Method for Medical Semantic Segmentation—0
Annotation-cost Minimization for Medical Image Segmentation using Suggestive Mixed Supervision Fully Convolutional Networks—0
Annotation-Efficient Learning for Medical Image Segmentation based on Noisy Pseudo Labels and Adversarial Learning—0
A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation—0
A Novel Domain Adaptation Framework for Medical Image Segmentation—0
A Novel Hybrid Parameter-Efficient Fine-Tuning Approach for Hippocampus Segmentation and Alzheimer's Disease Diagnosis—0
A novel shape-based loss function for machine learning-based seminal organ segmentation in medical imaging—0
A Point in the Right Direction: Vector Prediction for Spatially-aware Self-supervised Volumetric Representation Learning—0
Application of belief functions to medical image segmentation: A review—0
A Radiomics-Incorporated Deep Ensemble Learning Model for Multi-Parametric MRI-based Glioma Segmentation—0
A Recent Survey of Vision Transformers for Medical Image Segmentation—0
Are foundation models efficient for medical image segmentation?—0
A review: Deep learning for medical image segmentation using multi-modality fusion—0
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient—0
Artificial Intelligence-based algorithms in medical image scan seg-mentation and intelligent visual-content generation -- a concise overview—0
A Segmentation Foundation Model for Diverse-type Tumors—0
A Semantic Knowledge Complementarity based Decoupling Framework for Semi-supervised Class-imbalanced Medical Image Segmentation—0
A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset—0
ASLseg: Adapting SAM in the Loop for Semi-supervised Liver Tumor Segmentation—0
A sparse annotation strategy based on attention-guided active learning for 3D medical image segmentation—0
Assessing the Performance of the DINOv2 Self-supervised Learning Vision Transformer Model for the Segmentation of the Left Atrium from MRI Images—0
Assessing the Role of Random Forests in Medical Image Segmentation—0
A Study on the Use of Edge TPUs for Eye Fundus Image Segmentation—0
An image segmentation algorithm based on multi-scale feature pyramid network—0
A survey on shape-constraint deep learning for medical image segmentation—0
Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection—0
A Systematic Approach for MRI Brain Tumor Localization, and Segmentation using Deep Learning and Active Contouring—0
A temporal enhanced semi-supervised segmentation network for needle detection in 3D ultrasound images—0
A Transformer-based Generative Adversarial Network for Brain Tumor Segmentation—0
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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
4RaBiTmean Dice0.95—Unverified
5Yolo-SAM 2mean 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