We present a deep learning (DL)‐based automated whole lung and COVID‐19 pneumonia
infectious lesions (COLI‐Net) detection and segmentation from chest computed tomography …

An automatic method for qualitative and quantitative evaluation of chest Computed
Tomography (CT) images is essential for diagnosing COVID-19 patients. We aim to develop …

Recent research on COVID-19 suggests that CT imaging provides useful information to
assess disease progression and assist diagnosis, in addition to help understanding the …

The COVID‐19 pandemic is a global, national, and local public health concern which has
caused a significant outbreak in all countries and regions for both males and females …

Background Currently, there is an urgent need for efficient tools to assess the diagnosis of
COVID-19 patients. In this paper, we present feasible solutions for detecting and labeling …

COVID-19 is a fast-growing disease all over the world, but facilities in the hospitals are
restricted. Due to unavailability of an appropriate vaccine or medicine, early identification of …

Detecting COVID-19 at an early stage is essential to reduce the mortality risk of the patients.
In this study, a cascaded system is proposed to segment the lung, detect, localize, and …

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a global
threat impacting the lives of millions of people worldwide. Automated detection of lung …

Objective Computed tomography (CT) provides rich diagnosis and severity information of
COVID‐19 in clinical practice. However, there is no computerized tool to automatically …

Background: COVID-19 lung segmentation using Computed Tomography (CT) scans is
important for the diagnosis of lung severity. The process of automated lung segmentation is …