Abstract The Coronavirus (COVID-19) pandemic impelled several research efforts, from
collecting COVID-19 patients' data to screening them for virus detection. Some COVID-19 …

Downsampling operations such as max pooling or strided convolution are ubiquitously
utilized in Convolutional Neural Networks (CNNs) to aggregate local features, enlarge …

Since the emergence of the Covid-19 pandemic in late 2019, medical imaging has been
widely used to analyze this disease. Indeed, CT-scans of the lungs can help diagnose …

Automatic segmentation of the lung parenchyma from computed tomography (CT) images is
helpful for the subsequent diagnosis and treatment of patients. In this paper, based on a …

Objective Intracranial aneurysms (IA) are lethal, with high morbidity and mortality rates.
Reliable, rapid, and accurate segmentation of IAs and their adjacent vasculature from …

As lung cancer has emerged as the top contributor to cancer-related fatalities, efficient and
precise diagnostic methods are essential for efficient diagnosis. This research introduces a …

The coronavirus (COVID‐19) pandemic has had a terrible impact on human lives globally,
with far‐reaching consequences for the health and well‐being of many people around the …

The recent Coronavirus disease (COVID-19), which started in 2019, has spread across the
globe and become a global pandemic. The efficient and effective COVID-19 detection using …

Automatic diagnosis of Coronavirus disease 2019 (COVID-19) using chest computed
tomography (CT) images is of great significance for preventing its spread. However, it is …

In early 2020, the global spread of the COVID-19 has presented the world with a serious
health crisis. Due to the large number of infected patients, automatic segmentation of lung …