Thesis Abstract

Abstract
This thesis explores the utilization of artificial intelligence (AI) in radiography to enhance diagnostic accuracy in medical imaging. The integration of AI technologies into radiology has the potential to revolutionize the field by improving the efficiency and precision of image interpretation. The research aims to investigate the impact of AI on radiography practice, focusing on the benefits, challenges, and implications for healthcare delivery. Chapter One provides an introduction to the study, presenting the background, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. The chapter sets the foundation for the research by outlining the context and rationale for utilizing AI in radiography. Chapter Two comprises a comprehensive literature review that examines existing studies, articles, and reports related to the application of AI in radiography. The review covers ten key areas, including the evolution of AI in healthcare, current trends in radiology AI applications, and the potential benefits of AI integration in diagnostic imaging. Chapter Three outlines the research methodology employed in this study, detailing the research design, data collection methods, sampling techniques, data analysis procedures, and ethical considerations. The chapter provides a transparent overview of the research process, ensuring rigor and reliability in the findings. Chapter Four presents a detailed discussion of the research findings, highlighting the impact of AI technologies on diagnostic accuracy in radiography. The chapter analyzes the results of the study, identifies patterns and trends, and discusses the implications of AI integration for radiology practice. Chapter Five concludes the thesis by summarizing the key findings, discussing the implications for clinical practice, and offering recommendations for future research and implementation. The chapter emphasizes the potential of AI in radiography to enhance diagnostic accuracy, improve patient outcomes, and optimize healthcare delivery. In conclusion, this thesis contributes to the growing body of knowledge on the utilization of artificial intelligence in radiography for improved diagnostic accuracy. By exploring the benefits and challenges of AI integration in radiology practice, the research aims to inform healthcare professionals, policymakers, and researchers about the transformative potential of AI technologies in medical imaging.

Thesis Overview

The project titled "Utilization of Artificial Intelligence in Radiography for Improved Diagnostic Accuracy" focuses on the integration of artificial intelligence (AI) technology within the field of radiography to enhance diagnostic accuracy. Radiography plays a crucial role in medical imaging, allowing healthcare professionals to visualize internal structures and diagnose various medical conditions. However, interpreting radiographic images accurately can be challenging and time-consuming, leading to potential errors and delays in patient diagnosis and treatment. The integration of AI in radiography offers significant potential to address these challenges by providing automated image analysis, pattern recognition, and decision support tools. By leveraging machine learning algorithms and deep learning techniques, AI systems can analyze radiographic images quickly and accurately, assisting radiologists in detecting abnormalities, making diagnoses, and developing treatment plans. This project aims to explore the benefits and limitations of utilizing AI in radiography to improve diagnostic accuracy and optimize patient care. Key areas of focus within this research project include examining the current state of AI technology in radiography, identifying the specific tasks and applications where AI can enhance diagnostic accuracy, evaluating the performance of AI algorithms in analyzing radiographic images, and assessing the impact of AI integration on radiology practice and patient outcomes. Additionally, the project will investigate the challenges and ethical considerations associated with implementing AI in radiography, such as data privacy, algorithm transparency, and clinician acceptance. Through a comprehensive research overview, this project seeks to contribute to the growing body of knowledge on the utilization of AI in radiography and its potential to revolutionize medical imaging practices. By providing a detailed analysis of the benefits, limitations, and implications of AI technology in radiography, this research aims to inform healthcare professionals, policymakers, and industry stakeholders about the opportunities and challenges associated with adopting AI for improved diagnostic accuracy in radiology."