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Found 6 papers, 1 papers with code
Segmenting Bi-Atrial Structures Using ResNext Based Framework
Atrial fibrillation (AF) is the most common cardiac arrhythmia, significantly contributing to mortality, particularly in older populations.
How good nnU-Net for Segmenting Cardiac MRI: A Comprehensive Evaluation
Cardiac segmentation is a critical task in medical imaging, essential for detailed analysis of heart structures, which is crucial for diagnosing and treating various cardiovascular diseases.
Dynamic Position Transformation and Boundary Refinement Network for Left Atrial Segmentation
Specifically, we design a shuffle-then-reorder attention module to adjust the position of disrupted objects in the latent space using dynamic generation ratios, such that the vital dependencies among these random cropping targets could be well captured and preserved.
Integrating Deep Learning in Cardiology: A Comprehensive Review of Atrial Fibrillation, Left Atrial Scar Segmentation, and the Frontiers of State-of-the-Art Techniques
Atrial fibrillation (AFib) is the prominent cardiac arrhythmia in the world.
A 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 treatment.
Segmentation of histological images and fibrosis identification with a convolutional neural network
Segmentation of histological images is one of the most crucial tasks for many biomedical analyses including quantification of certain tissue type.
