Abstract:The diagnostic and radiological service, which is rated as a primary service, for the examination of internal diseases and the consequences of Covid-19, played a crucial role in examinations of patients with corona-virus. In this study, we aim to evaluate the important role that diagnostic imaging has played in dealing with the pandemic situation where, by means of X-ray imaging technologies, it has been possible to identify the severity of the disease in patients affected by Covid 19. With support of NASRI, under project "Development of simulation and forecasting models and integration with the TCIA database of medical images", we analysed the diagnostic system in several diagnostics centres in Albania. We used Piranha Multi (RTI Group) to verify the accuracy of the voltage (kV), the stability of the repetition of the values of the voltage dependence of the power voltage change, the overall filtering and the exposure time. We have presented a general picture of the situation of diagnostic equipment in Albania compared to OECD and COCIR indicators. The study shows that diagnostic imaging in Albania uses a large variety of equipment, but compared to the OECD standard, the ratio of units per 1 million inhabitants in Albania is below the average number. We found a low level of compliance with the COCIR standards ("Golden Rules") where more than 65% of the basic equipment installed is between six and ten years old, 20% is less than five years old and 15% of the installed equipment is more than ten years old.
After several months of tiresome work, we are nearing the finalization of the project for the application of Artificial Intelligence in medical imaging. It is a privilege for our working group to present today some of the results of our work at the international conference: "International Conference on Artificial Intelligence in Medical Application 8-9 June 2023, Hamburg, Germany".
Thanks to the support of the National Agency for Scientific Research and Innovation #AKKSHI and Research Expertise from the Academic Diaspora #READ, we managed to get to know each other and become part of the network of professionals working in this direction! Our works: " Using Deep Convolutional Neural Network to create a DCNN model for brain tumor detection" and "MRI image segmentation with HD Brain Extraction extension in 3D Slicer", were part of discussions with other collegaues. New collaborations are comming: #artificialintelligence
#UPT, #FIMIF, #AKKSHI, #READ, #EFOMP