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.
Because of the increased use of ionizing radiation, radiation management and security procedures are now regarded a standard part of many therapeutic and specialist fields. The focus of this work is on the radiation security features of Novel Oxide Glass (PZBKTANEr). The unique glass assembly is 40P2O5-30ZnO- 20BaF2-3.8K2TeO3- 1.2Al2O3-5Nb2O5-3Er2O3 in mol percent (test code PZBKTANEr). For the suggested oxide glass, several radiation shielding characteristics have been investigated for a specific energy range of ionizing radiation. The linear and mass attenuation coefficients, mean free path, half-value layer, total nuclear and electronic cross-sections, and fast neutron expulsion cross-section are among the radiation shielding properties. Furthermore, the unique fabricated glass (PZBKTANEr) was compared to commonly used radiation protection compositions, such as RS-253 G18, RS-360, RS-520, Chromite, Ferrite, Magnetite, and Barite glass, as well as RS-253 G18, RS-360, RS-520, Chromite, Ferrite, Magnetite, and Barite glass. Also, we studied the structure of fabrication by using Raman spectra. The findings suggest that the new oxide glass might be used in a broad variety of ionizing radiation applications for protection in both therapeutic and industrial applications.
In numerous tissue engineering and dental applications, bioactive glasses are utilized. These glasses have unique characteristics that make them attractive candidates for a variety of applications. A new bioactive glass system with the structure of 45P2O5 − 20CaO − 15CaCL2 − 8KF − (10 − x) Li2O − (x) TiO2 was developed in this study, with x = 2, 6, and 8 mol%. For usage in radiation protective applications, it was evaluated. By using an ultraviolet–visible spectrophotometer, we were able to measure the absorbance (Abs) and transmittance (T %) in the range of wavelengths 190–2500 nm. Furthermore, the optical energy gap of the produced glasses was determined. Using the MIKE software, the mass attenuation coefficients (MAC) of the bioactive glasses under investigation were calculated for energies ranging from 15 to 200 keV. The 𝐿𝐿𝐿𝐿𝐿𝐿, 𝑍𝑍𝑒𝑒𝑒𝑒𝑒𝑒, 𝑁𝑁𝑒𝑒𝑒𝑒𝑒𝑒, 𝐻𝐻𝐻𝐻𝐻𝐻, 𝑇𝑇𝑇𝑇𝑇𝑇, 𝑎𝑎𝑎𝑎𝑎𝑎 𝑀𝑀𝑀𝑀𝑀𝑀 (Linear attenuation coefficient, effective atomic number, effective electron density, half value layer, tenth value layer, and mean free path) of the bioactive glasses were calculated. According to the findings, the addition of titanium dioxide (TiO2) as well as the metal oxide such as Li2O to bioactive glasses generates significant differences in the attenuation characteristics of bioactive glasses. The results indicate that the PCKLT3( 𝑇𝑇𝑇𝑇𝑇𝑇2= 8mol%) bioactive-glass sample had the best attenuation among other samples.
Objectives: Since late 2019, Coronavirus Disease 2019 (COVID-19) has spread around the world. It has been determined that the disease is very contagious and can cause acute respiratory distress (ARD). Medical imaging has the potential to help identify, detect, and quantify the severity of this infection. This work seeks to develop a novel auto-detection technique for verified COVID-19 cases that can detect aberrant alterations in traditional X-ray pictures. Methods: Nineteen separate-colored layers were created from X ray scans of patients diagnosed with COVID-19. Each layer represents objects that have a similar contrast and can be represented by a single color. On a single layer, objects with similar contrasts are formed. A single color image was created by extracting all the objects from all the layers. The prototype model could recognize a wide range of abnormal changes in the image texture based on color differentiation. This was true even when the contrast values of the detected uncleared abnormalities varied a little. Results: The results indicate that the proposed novel method is 91% accurate in detecting and grading COVID-19 lung infection when compared to the opinions of three experienced radiologists evaluating chest X-ray images. Additionally, the method can be used to determine the infection site and severity of the disease by categorizing the X-rays into five severity levels. Conclusion: By comparing affected tissue to healthy tissue, the proposed COVID-19 auto-detection method can identify locations and indicate the severity of the disease, as well as predict where the disease may spread.
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