Thesis Abstract

Abstract
This thesis explores the utilization of artificial intelligence (AI) in the field of radiography image analysis. The integration of AI technologies in healthcare has shown promising results in improving diagnostic accuracy, efficiency, and patient outcomes. The focus of this study is to investigate the application of AI algorithms in processing and interpreting radiographic images for enhanced diagnostic capabilities. The introduction provides a background of the study, highlighting the growing importance of AI in healthcare and specifically in radiography. The problem statement identifies the challenges faced in traditional radiographic image analysis methods, emphasizing the need for more advanced and efficient techniques. The objectives of the study are to evaluate the effectiveness of AI algorithms in radiography image analysis and to assess the impact of AI on diagnostic accuracy and efficiency. The literature review covers ten key areas related to AI in radiography, including the evolution of AI in healthcare, current applications of AI in radiology, and the benefits and challenges of implementing AI in radiography image analysis. The review synthesizes existing research and highlights gaps in the literature that this study aims to address. The research methodology section outlines the approach taken in conducting this study, including the selection of AI algorithms, data collection methods, image processing techniques, and evaluation criteria. The methodology also discusses ethical considerations and limitations of the study. The discussion of findings chapter presents a detailed analysis of the results obtained from applying AI algorithms to radiography image analysis. The findings are interpreted in the context of the research objectives and compared with existing literature to draw meaningful conclusions. In conclusion, this thesis provides insights into the potential of AI in revolutionizing radiography image analysis. The study demonstrates the benefits of AI technology in improving diagnostic accuracy, reducing interpretation time, and enhancing overall patient care. The implications of this research extend to healthcare providers, researchers, and policymakers seeking to leverage AI for enhancing radiography practices. Keywords artificial intelligence, radiography, image analysis, healthcare, diagnostic accuracy, machine learning, deep learning, data analysis, radiology, technology.

Thesis Overview