Thesis Abstract

Abstract
Radiography is a critical diagnostic imaging technique used in the medical field for capturing images of internal body structures. The advancements in Artificial Intelligence (AI) have provided opportunities to enhance radiography through automated image analysis. This thesis explores the integration of AI in radiography to improve the efficiency and accuracy of image interpretation. The research begins with a comprehensive introduction outlining the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. The literature review in Chapter Two delves into ten key studies related to AI applications in radiography, highlighting the benefits and challenges associated with automated image analysis. Chapter Three focuses on the research methodology, detailing the research design, data collection methods, AI algorithms utilized, image processing techniques, validation process, and ethical considerations. The methodology aims to provide a robust framework for implementing AI in radiography for automated image analysis. In Chapter Four, the discussion of findings presents a detailed analysis of the results obtained from applying AI in radiography. The chapter explores the effectiveness of AI algorithms in image analysis, compares AI-assisted diagnosis with traditional methods, discusses the implications for radiography practice, and addresses potential areas for future research. The conclusion and summary in Chapter Five consolidate the key findings of the research, emphasizing the significance of integrating AI in radiography for automated image analysis. The thesis underscores the importance of leveraging AI technologies to enhance diagnostic accuracy, improve patient outcomes, and streamline radiography processes. Overall, this thesis contributes to the growing body of knowledge on the use of Artificial Intelligence in radiography for automated image analysis. By harnessing the power of AI, radiographers and healthcare professionals can optimize image interpretation, expedite diagnosis, and ultimately provide better care for patients. This research sets the stage for further advancements in AI applications within the field of radiography, paving the way for a more efficient and effective healthcare system.

Thesis Overview