Application of Artificial Intelligence in Enhancing Image Quality in Radiography

Thesis Abstract

Abstract
This thesis explores the utilization of Artificial Intelligence (AI) to enhance image quality in the field of radiography. The rapid advancements in AI technology have opened up new possibilities for improving the accuracy and efficiency of radiographic imaging procedures. This research aims to investigate the potential benefits of integrating AI algorithms into radiography practices to enhance image quality and optimize diagnostic outcomes. The study begins with a comprehensive review of existing literature on AI applications in radiography, highlighting the current trends, challenges, and opportunities in this rapidly evolving field. The literature review covers various AI techniques, such as machine learning, deep learning, and computer vision, that have shown promise in enhancing image quality in radiography. Following the literature review, the research methodology section outlines the approach taken to evaluate the effectiveness of AI in improving image quality in radiography. The methodology includes the selection of appropriate AI algorithms, data collection methods, and evaluation criteria to measure the impact of AI on image quality enhancement. The findings of the study reveal significant improvements in image quality achieved through the application of AI algorithms. The results demonstrate that AI can enhance image clarity, reduce noise artifacts, and improve the overall diagnostic accuracy of radiographic images. Moreover, the study highlights the potential for AI to streamline radiography workflows, leading to faster image processing and reduced human errors. The discussion section delves into the implications of these findings for the field of radiography, emphasizing the transformative potential of AI in revolutionizing image quality standards. The discussion also addresses the limitations and challenges associated with implementing AI solutions in radiography, such as data privacy concerns, algorithm biases, and regulatory issues. In conclusion, this thesis underscores the significance of leveraging AI technologies to enhance image quality in radiography. The study contributes valuable insights into the practical applications of AI in radiographic imaging and provides recommendations for further research and development in this area. By harnessing the power of AI, radiography professionals can unlock new possibilities for improving patient care, diagnostic accuracy, and overall healthcare outcomes.