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 …
Deep learning in cardiology
P Bizopoulos, D Koutsouris - IEEE reviews in biomedical …, 2018 - ieeexplore.ieee.org
The medical field is creating large amount of data that physicians are unable to decipher
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac
magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish …
magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish …
Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers
Deep fully convolutional neural network (FCN) based architectures have shown great
potential in medical image segmentation. However, such architectures usually have millions …
potential in medical image segmentation. However, such architectures usually have millions …
Automatic cardiac disease assessment on cine-MRI via time-series segmentation and domain specific features
Cardiac magnetic resonance imaging improves on diagnosis of cardiovascular diseases by
providing images at high spatiotemporal resolution. Manual evaluation of these time-series …
providing images at high spatiotemporal resolution. Manual evaluation of these time-series …
Cardiac segmentation with strong anatomical guarantees
Convolutional neural networks (CNN) have had unprecedented success in medical imaging
and, in particular, in medical image segmentation. However, despite the fact that …
and, in particular, in medical image segmentation. However, despite the fact that …
Deep learning-based cardiovascular image diagnosis: a promising challenge
Artificial intelligence (AI) is becoming a vital concept in medicine leading to a rapid
emergence of important tools for medical diagnostics. Now, as a crucial machine learning …
emergence of important tools for medical diagnostics. Now, as a crucial machine learning …
Convolutional neural network with shape prior applied to cardiac MRI segmentation
In this paper, we present a novel convolutional neural network architecture to segment
images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed …
images from a series of short-axis cardiac magnetic resonance slices (CMRI). The proposed …
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 …
High-level prior-based loss functions for medical image segmentation: A survey
Today, deep convolutional neural networks (CNNs) have demonstrated state of the art
performance for supervised medical image segmentation, across various imaging modalities …
performance for supervised medical image segmentation, across various imaging modalities …