Magnetic particle imaging (MPI) has recently emerged as a promising non-invasive imaging
technique because of its signal linearly propotional to the tracer mass, ability to generate …

Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …

Background A categorical CT assessment scheme for suspicion of pulmonary involvement
of coronavirus disease 2019 (COVID-19 provides a basis for gathering scientific evidence …

With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer
death in the United States. Lung cancer screening using low-dose computed tomography …

Magnetic particle imaging (MPI) is a novel emerging noninvasive and radiation-free imaging
modality that can quantify superparamagnetic iron oxide nanoparticles tracers. The zero …

Lung cancer computed tomography (CT) screening trials using low-dose CT have
repeatedly demonstrated a reduction in the number of lung cancer deaths in the screening …

The implementation of low-dose chest CT for lung screening presents a crucial opportunity
to advance lung cancer care through early detection and interception. In addition, millions of …

Purpose To determine whether deep learning algorithms developed in a public competition
could identify lung cancer on low-dose CT scans with a performance similar to that of …

Purpose To develop a radiomics nomogram based on computed tomography (CT) images
that can help differentiate lung adenocarcinomas and granulomatous lesions appearing as …

OBJECTIVE. The objective of our study was to assess the effect of the combination of deep
learning–based denoising (DLD) and iterative reconstruction (IR) on image quality and Lung …