A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
Deep learning for cardiac image segmentation: a review
Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
Uncertainty-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 …
data. However, it is expensive and time-consuming to annotate data for medical image …
Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation
Recent advances in deep learning for medical image segmentation demonstrate expert-
level accuracy. However, application of these models in clinically realistic environments can …
level accuracy. However, application of these models in clinically realistic environments can …
Med3d: Transfer learning for 3d medical image analysis
The performance on deep learning is significantly affected by volume of training data.
Models pre-trained from massive dataset such as ImageNet become a powerful weapon for …
Models pre-trained from massive dataset such as ImageNet become a powerful weapon for …
A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging
Segmentation of medical images, particularly late gadolinium-enhanced magnetic
resonance imaging (LGE-MRI) used for visualizing diseased atrial structures, is a crucial first …
resonance imaging (LGE-MRI) used for visualizing diseased atrial structures, is a crucial first …
Artificial intelligence and machine learning in arrhythmias and cardiac electrophysiology
Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of
intense exploration, showing potential to automate human tasks and even perform tasks …
intense exploration, showing potential to automate human tasks and even perform tasks …
Advances in deep learning-based medical image analysis
Importance. With the booming growth of artificial intelligence (AI), especially the recent
advancements of deep learning, utilizing advanced deep learning-based methods for …
advancements of deep learning, utilizing advanced deep learning-based methods for …
Context-aware network fusing transformer and V-Net for semi-supervised segmentation of 3D left atrium
C Zhao, S **ang, Y Wang, Z Cai, J Shen, S Zhou… - Expert Systems with …, 2023 - Elsevier
Accurate, robust and automatic segmentation of the left atrium (LA) in magnetic resonance
images (MRI) is of great significance for studying the LA structure and facilitating the …
images (MRI) is of great significance for studying the LA structure and facilitating the …
Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …