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 …
A review on bayesian deep learning in healthcare: Applications and challenges
In the last decade, Deep Learning (DL) has revolutionized the use of artificial intelligence,
and it has been deployed in different fields of healthcare applications such as image …
and it has been deployed in different fields of healthcare applications such as image …
Confidence calibration and predictive uncertainty estimation for deep medical image segmentation
Fully convolutional neural networks (FCNs), and in particular U-Nets, have achieved state-of-
the-art results in semantic segmentation for numerous medical imaging applications …
the-art results in semantic segmentation for numerous medical imaging applications …
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 …
[HTML][HTML] Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with
respect to the quantity of high-performing solutions reported in the literature. End users are …
respect to the quantity of high-performing solutions reported in the literature. End users are …
Multiscale attention guided U-Net architecture for cardiac segmentation in short-axis MRI images
Abstract Background and Objective: Automatic cardiac segmentation plays an utmost role in
the diagnosis and quantification of cardiovascular diseases. Methods: This paper proposes …
the diagnosis and quantification of cardiovascular diseases. Methods: This paper proposes …
Analyzing the quality and challenges of uncertainty estimations for brain tumor segmentation
Automatic segmentation of brain tumors has the potential to enable volumetric measures
and high-throughput analysis in the clinical setting. Reaching this potential seems almost …
and high-throughput analysis in the clinical setting. Reaching this potential seems almost …
Recent advances in fibrosis and scar segmentation from cardiac MRI: a state-of-the-art review and future perspectives
Segmentation of cardiac fibrosis and scars is essential for clinical diagnosis and can provide
invaluable guidance for the treatment of cardiac diseases. Late Gadolinium enhancement …
invaluable guidance for the treatment of cardiac diseases. Late Gadolinium enhancement …
Automatic segmentation with detection of local segmentation failures in cardiac MRI
Segmentation of cardiac anatomical structures in cardiac magnetic resonance images
(CMRI) is a prerequisite for automatic diagnosis and prognosis of cardiovascular diseases …
(CMRI) is a prerequisite for automatic diagnosis and prognosis of cardiovascular diseases …
Toward high-throughput artificial intelligence-based segmentation in oncological PET imaging
An array of artificial intelligence (AI) techniques in the field of medical imaging has emerged
in the past decade for automated image segmentation. 1 Medical image segmentation seeks …
in the past decade for automated image segmentation. 1 Medical image segmentation seeks …