Project Abstract

Abstract
This research project aims to explore the potential of utilizing artificial intelligence (AI) for the automated detection of pathologies in radiographic images. The field of radiography plays a crucial role in the diagnosis and treatment of various medical conditions, and the accurate interpretation of radiographic images is essential for providing effective healthcare services. However, the process of manually analyzing radiographic images to detect pathologies can be time-consuming and prone to human error. The integration of AI technologies into radiography has the potential to revolutionize the way radiographic images are interpreted and analyzed. By leveraging machine learning algorithms and deep learning techniques, AI systems can be trained to identify and classify different types of pathologies in radiographic images with a high degree of accuracy. This automated approach has the potential to significantly reduce the time and effort required for radiologists to analyze images, leading to faster diagnosis and treatment for patients. The research will begin with a comprehensive review of the existing literature on the application of AI in radiography and the automated detection of pathologies in medical images. This literature review will provide a solid foundation for understanding the current state of the art in AI technologies and their potential benefits in the field of radiography. The research methodology will involve collecting and analyzing a dataset of radiographic images containing various pathologies. This dataset will be used to train and evaluate AI models for automated pathology detection. The methodology will also include the selection of appropriate machine learning algorithms, data preprocessing techniques, and model evaluation metrics to ensure the accuracy and reliability of the AI system. The findings of the research will be presented and discussed in detail in Chapter Four, focusing on the performance of the AI models in detecting different types of pathologies in radiographic images. The discussion will also highlight the strengths and limitations of the AI system and propose recommendations for further improvement and future research directions. In conclusion, this research project will contribute to the advancement of AI technologies in radiography and provide valuable insights into the potential benefits of automated pathology detection in medical imaging. By harnessing the power of AI, healthcare providers can enhance the quality and efficiency of diagnostic services, ultimately leading to improved patient outcomes and better healthcare delivery.

Project Overview