Project Abstract

This project aims to explore the crucial domain of radiation dose optimization in computed tomography (CT) imaging, a field of growing importance in the healthcare industry. Computed tomography has become an indispensable diagnostic tool, providing healthcare professionals with detailed, high-resolution images that enable accurate diagnosis and effective treatment planning. However, the ionizing radiation associated with CT scans has raised significant concerns regarding patient safety, particularly with the increasing frequency of CT examinations. The primary objective of this project is to investigate and evaluate various radiation dose optimization techniques that can be employed in CT imaging to reduce the radiation exposure to patients without compromising the diagnostic quality of the images. This is of paramount importance, as excessive radiation exposure can lead to an increased risk of cancer and other health complications, particularly in vulnerable populations such as children and pregnant women. The study will begin with a comprehensive review of the current state of the art in radiation dose optimization techniques, including but not limited to, automated exposure control, iterative reconstruction algorithms, and dose-modulating scan protocols. This literature review will provide a solid foundation for understanding the theoretical underpinnings and practical applications of these techniques, as well as their respective strengths and limitations. The project will then focus on the implementation and evaluation of these radiation dose optimization techniques in a clinical setting. This will involve collaboration with healthcare facilities, radiologists, and medical physicists to acquire and analyze CT image data from a diverse set of patients and clinical scenarios. The research team will carefully assess the impact of the optimization techniques on various image quality metrics, such as noise, contrast, and spatial resolution, as well as on the overall radiation dose received by the patients. To ensure the reliability and validity of the findings, the project will employ a combination of experimental and computational approaches. This may include the use of anthropomorphic phantoms, Monte Carlo simulations, and advanced image analysis algorithms to quantify the performance of the optimization techniques under controlled conditions and across different CT scanner models and protocols. The results of this project will have far-reaching implications for the healthcare industry, as they will provide healthcare professionals with evidence-based guidance on the most effective radiation dose optimization strategies to employ in their daily practice. By reducing the radiation exposure to patients, this research has the potential to enhance patient safety, improve diagnostic accuracy, and ultimately contribute to better healthcare outcomes. Furthermore, the insights gained from this project may also inform the development of new CT imaging technologies and the refinement of existing ones, fostering innovation and progress in the field of medical imaging. The dissemination of the project's findings through peer-reviewed publications and conference presentations will ensure that the knowledge gained is widely shared and can be leveraged by the broader scientific community. In conclusion, this project represents a crucial step in addressing the challenge of radiation dose optimization in computed tomography imaging. By employing a comprehensive, multifaceted approach, the research team aims to deliver tangible solutions that can be effectively implemented in clinical practice, ultimately enhancing patient safety and the overall quality of healthcare.

Project Overview