Thesis (Ph. D.)--Worcester Polytechnic Institute. / Keywords: Detector design and characterization; modulation transfer function; digital fluoroscopy. Includes bibliographical references (p. 150-160).

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Coded-aperture imaging without detector motion can be used to reconstruct three-dimensional radionuclide distributions in the context of nuclear medicine. This approach offers several advantages over the rotating gamma-ray camera systems presently employed in the clinic. These advantages include improved sensitivity, potentially better spatial resolution, and the capability of doing dynamic studies. There are two problems associated with the coded-aperture approach, however. First, the data is "multiplexed", which refers to the fact that many line integrals of the source distribution are combined together and not measured individually, so that information is lost. Second, the number of resolvable detector elements is typically an order of magnitude less than the number of object elements to be reconstructed, so that the reconstruction problem is underdetermined. Consequently, the reconstruction is not unique. By using various types of a priori information in forming the reconstruction, however, it is possible to augment the incomplete data set. Two algorithms are presented to reconstruct objects from their coded-image projections and various types of a priori information. The first, a Monte Carlo algorithm, is a flexible and computationally efficient approach using the a priori knowledge of positivity and nearest-neighbor correlation. This algorithm is used to qualitatively explore the effect of the data-taking geometry on reconstruction performance. The second algorithm is a linear estimator incorporating as a priori knowledge completely general first- and second-order statistical information about the object class to be reconstructed. The linear-estimator formalism also provides a minimum-variance expression for system optimization. This linear algorithm is used to explore the effects of correct and incorrect a priori information on reconstruction performance, and to quantitatively investigate reconstruction quality with respect to data-taking geometry.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

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No description available.

From one treatment to the next, considerable effort is made to accurately position radiotherapy patients according to their treatment plans. However, some variation is unavoidable. The target volume and the organs at risk may also move within the patient and/or change shape during the treatment. Thus, it is important to be able to verify the success of the treatment by determining the position of patient and the dose deposited in the patient at each fraction. One possibility to achieve this, particularly when equipment, time and budgets are limited, would be to collect limited information while the patient is on the treatment couch. This research was aimed to develop a method for optimum beam position determination, for each patient-specific case. The optimized beam positions would balance the both treatment planning and image reconstruction, so that the patient???s image can be obtained during the treatment delivery using the information collected from the same angles as used for treatment. This will allow verification of the dose deposited in the patient for every fraction. Using a limited number of angles for image reconstruction, the dose to the patient can be minimized. This work has two major parts, beam position optimization for image reconstruction and beam position optimization for treatment planning. These two optimizations are then combined to obtain the optimum beam position for both image reconstruction and treatment planning. An objective function, projection correlation, was developed to investigate the image reconstruction method using limited information. Another objective function, the average optimization quality factor, was also introduced to optimize beam positions for treatment planning. Two optimization methods, the gradient descent method and the simulated annealing based on these objective functions were used to determine the beam angles. The results show that the projection correlation presents several advantages. It can be applied without any iterations, and it produces a fast algorithm. The present research will allow selection of the optimum beam positions without excessive computational cost for treatment planning and imaging. By combining the projection correlation and the average optimization quality factor together with more advanced image reconstruction software this could potentially be used in a clinical environment.

Thesis (Ph.D.)--Tufts University, 2004. / Adviser: Sergio Fantini. Submitted to the Dept. of Electrical Engineering. Includes bibliographical references (leaves 201-202). Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Thesis (Ph. D.)--University of Washington, 1990. / Vita. Includes bibliographical references (leaves [174]-182).