Background: Automated image segmentation is an essential step in quantitative image
analysis. This study assesses the performance of a deep learning-based model for lung …

This study aimed to evaluate the performance of a novel unsupervised deep learning-based
framework for automated infections lesion segmentation from CT images of Covid patients …

A rare-earth trihalide scintillator, CeBr3, in 1 cm edge cubic monocrystal form, is examined
with regard to its principal luminescence and scintillation properties, as a candidate for …

In beam geometries where a directed γ-ray beam hits the surface of a coaxial high purity
germanium detector (HPGe), the detector efficiency is sensitive to the position where γ-rays …

In clearance measurements involving a single material type, a conversion factor was applied
to convert measurement results to activity based on an assumed uniform density. However …

Multienergy computed tomography (CT) can be implemented based on traditional CT
systems to reduce the hardware cost. However, prior knowledge of the X-ray spectra or …

High-resolution photon-counting detector (PCD) computed tomography (CT) imaging is
increasingly used for several applications. Recent technological advances in CT …

In recent decades, a large worldwide research program has been launched to develop new
neutron detection technologies. The objective is to replace 3He gas neutron detectors …

Low-dose CT imaging has been proposed to reduce radiation dose to patients, and deep
learning-based algorithms have been used to restore the original quality and …

BackgroundThe total dose effect of ionization on satellites in Geostationary Earth Orbit
(GEO) is caused by space particle radiation in GEO. PurposeThis study aims to combine …