Thesis Abstract

The advancement of artificial intelligence (AI) has opened up new possibilities in various fields, including healthcare. In the field of radiography, AI has the potential to revolutionize the diagnostic process by improving accuracy and efficiency. This thesis explores the application of AI in radiography to enhance diagnostic accuracy. The study begins with an introduction to the topic, providing background information on the use of AI in healthcare and radiography. The problem statement highlights the challenges faced in traditional diagnostic methods and the potential benefits of integrating AI technology. The objectives of the study are outlined to investigate the impact of AI on diagnostic accuracy in radiography. Limitations and scope of the study are also discussed to provide a clear understanding of the research boundaries. Chapter two consists of a comprehensive literature review that examines existing studies and research on AI in radiography. The review covers topics such as AI algorithms, image processing techniques, and their application in medical imaging. The research methodology in chapter three outlines the approach taken to investigate the effectiveness of AI in improving diagnostic accuracy. This includes data collection methods, study design, and analysis techniques. The chapter also discusses ethical considerations and potential biases in AI algorithms. Chapter four presents the findings of the study, analyzing the impact of AI on diagnostic accuracy in radiography. The discussion covers the strengths and limitations of AI technology, as well as its implications for healthcare professionals and patients. The results are compared to traditional diagnostic methods to evaluate the effectiveness of AI in improving accuracy and efficiency. In the concluding chapter five, the thesis summarizes the key findings and conclusions drawn from the study. The significance of the research is discussed in relation to its contribution to the field of radiography and healthcare. Recommendations for future research and practical implications for implementing AI in radiography are also provided. Overall, this thesis contributes to the growing body of knowledge on the application of AI in radiography and its potential to enhance diagnostic accuracy, ultimately improving patient outcomes.

Thesis Overview

The project titled "Application of Artificial Intelligence in Radiography for Improved Diagnostic Accuracy" aims to explore the integration of artificial intelligence (AI) in radiography to enhance diagnostic accuracy in medical imaging. This research seeks to address the growing need for more precise and efficient diagnostic processes in radiology, which play a crucial role in patient care and treatment decisions. Radiography is a vital medical imaging technique used to visualize the internal structures of the body for diagnostic purposes. However, traditional radiographic interpretation relies heavily on human expertise, which can be prone to errors, inconsistencies, and subjectivity. By leveraging AI technology, this project intends to augment the capabilities of radiographers and radiologists in interpreting images accurately and quickly, ultimately leading to improved patient outcomes. The research will delve into the various applications of AI in radiography, such as image recognition, pattern recognition, and computer-aided diagnosis. By analyzing a wide range of literature, case studies, and existing research, this study aims to identify the benefits and challenges associated with integrating AI into radiographic practices. Furthermore, the project will focus on the development and validation of AI algorithms specifically tailored for radiography, considering factors such as image quality, data acquisition, and clinical relevance. Through the implementation of AI models, the research intends to enhance the speed, accuracy, and reliability of diagnostic interpretations, thereby reducing the likelihood of misdiagnoses and improving patient care. Additionally, the study will explore the ethical considerations, regulatory requirements, and potential limitations of implementing AI technology in radiography. By addressing these critical aspects, the research aims to provide insights into the responsible and effective utilization of AI tools in the healthcare domain. Overall, the project "Application of Artificial Intelligence in Radiography for Improved Diagnostic Accuracy" seeks to contribute to the advancement of radiographic practices by harnessing the power of AI to enhance diagnostic accuracy, streamline workflow efficiency, and ultimately improve patient care in the field of medical imaging.