Thesis Abstract

Abstract
The integration of artificial intelligence (AI) in radiography has revolutionized the field by enhancing diagnostic accuracy, efficiency, and patient outcomes. This thesis explores the impact of AI in radiography through a comparative study, analyzing its effectiveness in comparison to traditional radiographic techniques. The study aims to evaluate the benefits and limitations of AI in radiography, addressing key challenges and opportunities in the field. Chapter 1 provides an introduction to the research topic, discussing the background of the study, problem statement, objectives, limitations, scope, significance, and the structure of the thesis. The definitions of key terms related to AI and radiography are also outlined to establish a common understanding. Chapter 2 presents a comprehensive literature review on AI in radiography, covering ten key themes such as the evolution of AI in healthcare, applications of AI in radiography, benefits of AI technology, challenges in implementation, ethical considerations, and current trends in the field. The review synthesizes existing research to provide a holistic view of the topic. Chapter 3 details the research methodology employed in the comparative study, including research design, data collection methods, sample selection criteria, data analysis techniques, and ethical considerations. The chapter outlines the steps taken to ensure the validity and reliability of the study results. Chapter 4 presents an in-depth discussion of the study findings, comparing the effectiveness of AI-assisted radiography with traditional methods. The chapter analyzes the impact of AI on diagnostic accuracy, turnaround times, workflow efficiency, and patient outcomes, highlighting the strengths and limitations of AI technology in radiography. Chapter 5 concludes the thesis by summarizing the key findings, implications, and recommendations for future research and practice. The chapter reflects on the significance of the study in advancing the field of radiography through the integration of AI technology, emphasizing the need for ongoing research and innovation in this rapidly evolving area. In conclusion, this thesis contributes to the growing body of knowledge on the impact of artificial intelligence in radiography, providing insights into the benefits and challenges associated with AI technology in healthcare. The study underscores the transformative potential of AI in improving radiographic practices and patient care, paving the way for continued advancements in the field.

Thesis Overview

The project titled "The Impact of Artificial Intelligence in Radiography: A Comparative Study" aims to explore and evaluate the role of artificial intelligence (AI) in the field of radiography. Radiography, as a crucial medical imaging technique, plays a significant role in diagnosing and monitoring various health conditions. With advancements in AI technology, there is a growing interest in its application within radiography to enhance efficiency, accuracy, and outcomes. This comparative study seeks to analyze the impact of AI in radiography by comparing traditional radiographic practices with AI-assisted radiography. The research will delve into the benefits, challenges, and implications of integrating AI technology in radiography procedures. By examining real-world case studies and data, the project aims to provide insights into the effectiveness and potential limitations of AI in radiography. Key components of the research will include a thorough literature review to establish the current landscape of AI in radiography, an exploration of different AI technologies utilized in radiographic imaging, and an assessment of the practical implications for healthcare professionals and patients. The study will also investigate the level of acceptance and adoption of AI in radiography settings, considering factors such as cost, training requirements, and workflow integration. Through a comparative analysis of AI-assisted radiography and traditional radiographic methods, this research seeks to identify the strengths and weaknesses of AI in improving diagnostic accuracy, reducing interpretation errors, and optimizing patient care. The project aims to contribute valuable insights to the ongoing discourse on the integration of AI in medical imaging practices, with a focus on radiography. Overall, this research overview highlights the importance of evaluating the impact of AI in radiography through a comparative study to enhance our understanding of the potential benefits and challenges associated with the adoption of AI technology in healthcare settings. By exploring these key aspects, the project aims to provide a comprehensive analysis of how AI is transforming the field of radiography and shaping the future of medical imaging practices.