Papers Left Atrium Segmentation
“Left Atrium Segmentation” 태그가 달린 논문 18편 · 필터 해제
Multi-Scale Feature Fusion with Image-Driven Spatial Integration for Left Atrium Segmentation from Cardiac MRI Images
Accurate segmentation of the left atrium (LA) from late gadolinium-enhanced magnetic resonance imaging plays a vital role in visualizing diseased atrial structures, enabling the diagnosis and management of cardiovascular…
feature selectionLeft Atrium SegmentationSegmentationSpecificitySDCL: Students Discrepancy-Informed Correction Learning for Semi-supervised Medical Image Segmentation
Semi-supervised medical image segmentation (SSMIS) has been demonstrated the potential to mitigate the issue of limited medical labeled data. However, confirmation and cognitive biases may affect the prevalent teacher-st…
Image SegmentationLeft Atrium SegmentationMedical Image SegmentationSegmentation+2Collaborative Learning for Annotation-Efficient Volumetric MR Image Segmentation
Background: Deep learning has presented great potential in accurate MR image segmentation when enough labeled data are provided for network optimization. However, manually annotating 3D MR images is tedious and time-cons…
Image SegmentationLeft Atrium SegmentationSegmentationSelf-Supervised Learning+1Competitive Ensembling Teacher-Student Framework for Semi-Supervised Left Atrium MRI Segmentation
Semi-supervised learning has greatly advanced medical image segmentation since it effectively alleviates the need of acquiring abundant annotations from experts and utilizes unlabeled data which is much easier to acquire…
Image SegmentationLeft Atrium SegmentationMedical Image SegmentationMRI segmentation+3Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image Segmentation
Consistency regularization and pseudo labeling-based semi-supervised methods perform co-training using the pseudo labels from multi-view inputs. However, such co-training models tend to converge early to a consensus, deg…
Image SegmentationLeft Atrium SegmentationMedical Image SegmentationSegmentation+3Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation
Medical image segmentation is a fundamental and critical step in many clinical approaches. Semi-supervised learning has been widely applied to medical image segmentation tasks since it alleviates the heavy burden of acqu…
Brain Tumor SegmentationImage SegmentationLeft Atrium SegmentationMedical Image Segmentation+4MisMatch: Calibrated Segmentation via Consistency on Differential Morphological Feature Perturbations with Limited Labels
Semi-supervised learning (SSL) is a promising machine learning paradigm to address the issue of label scarcity in medical imaging. SSL methods were originally developed in image classification. The state-of-the-art SSL m…
Decoderimage-classificationImage ClassificationImage Segmentation+5Parameter Decoupling Strategy for Semi-supervised 3D Left Atrium Segmentation
Consistency training has proven to be an advanced semi-supervised framework and achieved promising results in medical image segmentation tasks through enforcing an invariance of the predictions over different views of th…
Image SegmentationLeft Atrium SegmentationMedical Image SegmentationSegmentation+1Adaptive Hierarchical Dual Consistency for Semi-Supervised Left Atrium Segmentation on Cross-Domain Data
Semi-supervised learning provides great significance in left atrium (LA) segmentation model learning with insufficient labelled data. Generalising semi-supervised learning to cross-domain data is of high importance to fu…
Left Atrium SegmentationSegmentationHierarchical Consistency Regularized Mean Teacher for Semi-supervised 3D Left Atrium Segmentation
Deep learning has achieved promising segmentation performance on 3D left atrium MR images. However, annotations for segmentation tasks are expensive, costly and difficult to obtain. In this paper, we introduce a novel hi…
Left Atrium SegmentationSegmentationSemi-supervised Left Atrium Segmentation with Mutual Consistency Training
Semi-supervised learning has attracted great attention in the field of machine learning, especially for medical image segmentation tasks, since it alleviates the heavy burden of collecting abundant densely annotated data…
Image SegmentationLeft Atrium SegmentationMedical Image SegmentationPseudo Label+2Fully Automated Left Atrium Segmentation from Anatomical Cine Long-axis MRI Sequences using Deep Convolutional Neural Network with Unscented Kalman Filter
This study proposes a fully automated approach for the left atrial segmentation from routine cine long-axis cardiac magnetic resonance image sequences using deep convolutional neural networks and Bayesian filtering. The …
Left Atrium SegmentationSegmentationA Global Benchmark of Algorithms for Segmenting Late Gadolinium-Enhanced Cardiac Magnetic Resonance Imaging
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 treat…
BenchmarkingLeft Atrium SegmentationSegmentationUncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation
Training deep convolutional neural networks usually requires a large amount of labeled data. However, it is expensive and time-consuming to annotate data for medical image segmentation tasks. In this paper, we present a …
Image SegmentationLeft Atrium SegmentationMedical Image SegmentationSegmentation+1Mixture Modeling of Global Shape Priors and Autoencoding Local Intensity Priors for Left Atrium Segmentation
Difficult image segmentation problems, for instance left atrium MRI, can be addressed by incorporating shape priors to find solutions that are consistent with known objects. Nonetheless, a single multivariate Gaussian is…
Density EstimationImage SegmentationLeft Atrium SegmentationSegmentation+1Combating Uncertainty with Novel Losses for Automatic Left Atrium Segmentation
Segmenting left atrium in MR volume holds great potentials in promoting the treatment of atrial fibrillation. However, the varying anatomies, artifacts and low contrasts among tissues hinder the advance of both manual an…
Left Atrium SegmentationTransfer LearningPyramid Network with Online Hard Example Mining for Accurate Left Atrium Segmentation
Accurately segmenting left atrium in MR volume can benefit the ablation procedure of atrial fibrillation. Traditional automated solutions often fail in relieving experts from the labor-intensive manual labeling. In this …
Left Atrium SegmentationSegmentationDomain and Geometry Agnostic CNNs for Left Atrium Segmentation in 3D Ultrasound
Segmentation of the left atrium and deriving its size can help to predict and detect various cardiovascular conditions. Automation of this process in 3D Ultrasound image data is desirable, since manual delineations are t…
Domain AdaptationLeft Atrium SegmentationMedical Image AnalysisSegmentation