The application of shielding is one of the main protective measures in ionizing radiation safety. This paper addresses the influence of erbium oxide (Er 2 O 3 ) amount fraction on shielding properties of the glass system with compound formula 75TeO 2 -10Nb 2 O 5 -10ZnO-5PbO (TNZP). Addition of Er 2 O 3 portions increased samples densities from 5.57 to 5.65 g/cm 3 . The attenuation properties for the different TNZP-Er 2 O 3 samples were simulated using Phy-X/PSD software at vary wide energy ranged from 0.015 to 15 MeV. Various radiation shielding parameters were evaluated including; linear (LAC) and mass (MAC) attenuation coefficients, the half (HVL)-and tenth

Since late 2019, Coronavirus Disease 2019 (COVID-19) has spread all over the world. The disease is highly contagious, and it may lead to acute respiratory distress (ARD). Medical imaging can play an important role in classifying, detecting, and measuring the severity of the virus. This study aims to provide a novel auto-detection tool that can detect abnormal changes in conventional X-ray images for confirmed COVID-19 cases. X-ray images from patients diagnosed with COVID-19 were converted into 19 different colored layers. Each layer represented objects with similar contrast that could be defined as a specific color. The objects with similar contrasts were formed in a single layer. All the objects from all the layers were extracted as a single-color image. Based on the differentiation of colors, the prototype model was able to recognize a wide spectrum of abnormal changes in the image texture. This was true even if there was minimal variation of the contrast values of the detected uncleared abnormalities. The results indicate that the proposed novel method can detect and determine the degree of lung infection from COVID-19 with an accuracy of 91%, compared to the opinions of three experienced radiologists. The method can also efficiently determine the sites of infection and the severity of the disease by classifying the X-rays into five levels of severity. Thus, the proposed COVID-19 autodetection method can identify locations and indicate the degree of severity of the disease by comparing affected tissue with healthy tissue, and it can predict where the disease may spread.

A novel hand-held hybrid optical-gamma camera (HGC) has previously been described that is capable of displaying co-aligned images from both modalities in a single imaging system. Here, a dedicated NIR imaging system for NIR fluorescence surgical guidance has been developed for combination with the HGC . This work has evaluated the performance of two NIR fluorescence imaging systems using phantom studies, various fluorophores and various experimental configurations. The threshold detectable concentration of ICG and 800CW dyes were investigated for both systems. Bespoke lymph node phantoms simulating metastases and tissue-like layers were constructed to evaluate the detection capability. ICG could be detected at a minimum concentration of 1 μM for each camera. The lower thresholds for 800CW were 10−2 and 10−3 μM for the modified and NIR cameras, respectively. Both cameras were unable to detect small-sized targets within a 3 mm depth, but were able to identify larger targets as deep as 7 mm. Further improvements are required to optimise the NIR-fluorescence systems for subsequent combination with the HGC to undertake dual gamma-NIR fluorescence intraoperative imaging.