Medicine and Health Sciences Commons^™

An Information Theory Model For Optimizing Quantitative Magnetic Resonance Imaging Acquisitions, Drew Mitchell

Dissertations & Theses (Open Access)

Quantitative magnetic resonance imaging (qMRI) is a powerful group of imaging techniques with a growing number of clinical applications, including synthetic image generation in post-processing, automatic segmentation, and diagnosis of disease from quantitative parameter values. Currently, acquisition parameter selection is performed empirically for quantitative MRI. Tuning parameters for different scan times, tissues, and resolutions requires some measure of trial and error. There is an opportunity to quantitatively optimize these acquisition parameters in order to maximize image quality and the reliability of the previously mentioned methods which follow image acquisition.

The objective of this work is to introduce and evaluate a …

Framework For Algorithmically Optimizing Longitudinal Health Outcomes: Examples In Cancer Radiotherapy And Occupational Radiation Protection, Lydia Joyce Wilson

LSU Doctoral Dissertations

Background: Advancements in the treatment of non-infectious disease have enabled survival rates to steadily increase in recent decades (e.g., diabetes, heart disease, and cancer). Epidemiological studies have revealed that the treatments for these diseases can have life-threatening and/or life–altering effects. Thus, realizing the full beneficial potential of advanced treatments necessitates new tools to algorithmically consider all major components of the health outcome, including benefit and detriment. The goal of this dissertation was to develop a framework for improving projected health outcomes following planned radiation exposures in consideration of all beneficial and detrimental, early and late, and fatal and non-fatal …