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Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu
Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu
McKelvey School of Engineering Theses & Dissertations
X-ray computed tomography (CT) is an important and effective tool in medical and industrial imaging applications. The state-of-the-art methods to reconstruct CT images have had great development but also face challenges. This dissertation derives novel algorithms to reduce bias and metal artifacts in a wide variety of imaging modalities and increase performance in low-dose scenarios. The most widely available CT systems still use the single-energy CT (SECT), which is good at showing the anatomic structure of the patient body. However, in SECT image reconstruction, energy-related information is lost. In applications like radiation treatment planning and dose prediction, accurate energy-related information …
Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu
Multi-Dimensional Extension Of The Alternating Minimization Algorithm In X-Ray Computed Tomography, Jingwei Lu
McKelvey School of Engineering Theses & Dissertations
X-ray computed tomography (CT) is an important and effective tool in medical and industrial
imaging applications. The state-of-the-art methods to reconstruct CT images have had
great development but also face challenges. This dissertation derives novel algorithms to
reduce bias and metal artifacts in a wide variety of imaging modalities and increase performance
in low-dose scenarios.
The most widely available CT systems still use the single-energy CT (SECT), which is
good at showing the anatomic structure of the patient body. However, in SECT image
reconstruction, energy-related information is lost. In applications like radiation treatment
planning and dose prediction, accurate energy-related information …