Left Atrium Segmentation
9 papers with code • 1 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Left Atrium Segmentation
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Libraries
Use these libraries to find Left Atrium Segmentation models and implementationsMost implemented papers
Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation
yulequan/UA-MT
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We design a novel uncertainty-aware scheme to enable the student model to gradually learn from the meaningful and reliable targets by exploiting the uncertainty information.
Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
HiLab-git/DTC
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Such mutual consistency encourages the two decoders to have consistent and low-entropy predictions and enables the model to gradually capture generalized features from these unlabeled challenging regions.
MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations with Limited Labels
The state-of-the-art SSL methods in image classification utilise consistency regularisation to learn unlabelled predictions which are invariant to input level perturbations.
A Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging
bragancas/vnet_pytorch-atriaseg2018
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Segmentation of cardiac images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) widely used for visualizing diseased cardiac structures, is a crucial first step for clinical diagnosis and treatment.
Hierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation
Deep learning has achieved promising segmentation performance on 3D left atrium MR images.
Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data
Heye-SYSU/AHDC
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For the inter-domain learning, a consistency constraint is applied to the LAs modelled by two dual-modelling networks to exploit the complementary knowledge among different data domains.
Parameter Decoupling Strategy for Semi-supervised 3D Left Atrium Segmentation
bx0903/pdc
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Based on this, the feature extractor is constrained to encourage the consistency of probability maps generated by classifiers under diversified features.
Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
senyh/ucmt
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Combining the strengths of UMIX with CMT, UCMT can retain model disagreement and enhance the quality of pseudo labels for the co-training segmentation.
SDCL: Students Discrepancy-Informed Correction Learning for Semi-supervised Medical Image Segmentation
pascalcpp/sdcl
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Semi-supervised medical image segmentation (SSMIS) has been demonstrated the potential to mitigate the issue of limited medical labeled data.
