[HTML][HTML] 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
M Khened, VA Kollerathu, G Krishnamurthi - Medical image analysis, 2019 - Elsevier
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 …