Administrative and medical processes of the healthcare organizations are rapidly changing
because of the use of artificial intelligence (AI) systems. This change demonstrates the …

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 …

Since December 2019, the coronavirus disease (COVID-19) outbreak has caused many
death cases and affected all sectors of human life. With gradual progression of time, COVID …

Deep learning has been widely used for medical image segmentation and a large number of
papers has been presented recording the success of deep learning in the field. A …

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 …

The medical imaging literature has witnessed remarkable progress in high-performing
segmentation models based on convolutional neural networks. Despite the new …

In medical imaging, segmentation plays a vital role towards the interpretation of X-ray
images where salient features are extracted with the help of image segmentation. Without …

Delineation of the cardiac structures from 2D echocardiographic images is a common
clinical task to establish a diagnosis. Over the past decades, the automation of this task has …

Abstract Transparency in Machine Learning (ML), often also referred to as interpretability or
explainability, attempts to reveal the working mechanisms of complex models. From a …

Abstract Corona virus disease (COVID-19) acknowledged as a pandemic by the WHO and
mankind all over the world is vulnerable to this virus. Alternative tools are needed that can …