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.

Thesis Overview

The project titled "Application of Artificial Intelligence in Enhancing Image Quality in Radiography" aims to explore the potential benefits and challenges of integrating artificial intelligence (AI) technologies in the field of radiography to enhance image quality. In recent years, AI has shown promise in various industries for its ability to analyze data, identify patterns, and make predictions with high accuracy. By applying AI algorithms to radiography, there is a potential to improve the quality of medical images, leading to more accurate diagnostics and better patient outcomes. The research will begin with a comprehensive review of the existing literature on the use of AI in radiography, highlighting the current trends, challenges, and opportunities in this field. This literature review will provide a solid foundation for understanding the state of the art and identifying gaps in the research that need to be addressed. The methodology section will outline the approach taken to implement AI algorithms in enhancing image quality in radiography. This will involve selecting appropriate AI models, acquiring and preprocessing radiographic images, training the AI algorithms, and evaluating their performance in comparison to traditional image processing techniques. The findings from the research will be discussed in detail in the results section, focusing on the effectiveness of AI in enhancing image quality, the impact on diagnostic accuracy, and the overall benefits to healthcare providers and patients. The discussion will also address any limitations or challenges encountered during the implementation of AI in radiography. In conclusion, the research will summarize the key findings, implications, and recommendations for future research and practical applications of AI in radiography. By exploring the application of artificial intelligence in enhancing image quality in radiography, this project aims to contribute to the ongoing efforts to improve healthcare diagnostics and patient care through innovative technology solutions.