Thesis (M.S.)--Rochester Institute of Technology, 1982. / Typescript. Includes bibliographical references (leaves 88-90).

Thesis (M.S.)--University of Florida, 2002. / Title from title page of source document. Includes vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Florida, 2005. / Title from title page of source document. Document formatted into pages; contains 125 pages. Includes vita. Includes bibliographical references.

This study discusses reject film analyses (RFAs) before and after the implementation of a quality improvement intervention. RFAs were undertaken to investigate the effect of the introduction and use of exposure charts (ECs) on department and student reject rates of extremity radiographs. Methods: A quantitative comparative pre and post-treatment research design was used. Data was collected from the x-ray departments of two training hospitals in Windhoek, Namibia over a five month period. A retrospective RFA was conducted to determine the department and student reject rates for both departments before intervention. Emphasis was placed on exposure related reject films. ECs were compiled and introduced at Katutura State Hospital (venue B) by the researcher. The students were instructed to use these charts. At Windhoek Central Hospital (venue A) no ECs were used. A prospective RFA was conducted to establish department and student reject rates at both hospitals after the intervention at venue B. Results: During the retrospective phase the department reject rate for venue A was 21 percent while the student reject rate was 23 percent. At venue B 24 percent and 26 percent were scored respectively. Students at venue A produced rejected radiographs due to overexposure (49 percent) and underexposure (23 percent), whilst 37 percent was recorded for both causes at venue B. At venue A, 35 percent of films were rejected due to incorrect mAs selection, at venue B the figure was 42 percent. Undiagnostic radiographs due to inaccurate kV selection comprised 62 percent for venue A and 59 percent for venue B. During the prospective phase the department reject rate for venue A was 20 percent and that of the students was 19 percent. For venue B 12 percent and 11 percent were scored respectively. At venue A radiographs rejected due to over and underexposure were 43 percent and 33 percent respectively while those at venue B were 33 percent and 34 percent. Incorrect mAs selection caused 33 percent of discarded films at venue A and 38 percent at venue B. The figures for inaccurate kV selection were 68 percent and 62 percent for venues A and B. Conclusions: The introduction and use of ECs lowered the student reject rate at venue B in the prospective phase.

published_or_final_version / Dentistry / Master / Master of Dental Surgery

Diffusion-weighted image(DWI) and tractography have been developed for decades and are key elements in recent, large-scale efforts for mapping the human brain. The two techniques together provide us a unique possibility to access the macroscopic structure and connectivity of the human brain non-invasively and in vivo. The information obtained not only can help visualize brain connectivity and help segment the brain into different functional areas but also provides tools for understanding some major cognitive diseases such as multiple sclerosis, schizophrenia, epilepsy, etc. There are lots of efforts have been put into this area. On the one hand, a vast spectrum of tractography algorithms have been developed in recent years, ranging from deterministic approaches through probabilistic methods to global tractography; On the other hand, various mathematical models, such as diffusion tensor, multi-tensor model, spherical deconvolution, Q-ball modeling, have been developed to better exploit the acquisition dependent signal of Diffusion-weighted image(DWI). Despite considerable progress in this area, current methods still face many challenges, such as sensitive to noise, lots of false positive/negative fibers, incapable of handling complex fiber geometry and expensive computation cost. More importantly, recent researches have shown that, even with high-quality data, the results using current tractography methods may not be improved, suggesting that it is unlikely to obtain an anatomically accurate map of the human brain solely based on the diffusion profile. Motivated by these issues, this dissertation develops a global approach that incorporates anatomical validated geometric shape prior when reconstructing neuron fibers. The fiber tracts between regions of interest are initialized and updated via deformations based on gradients of the posterior energy defined in this paper. This energy has contributions from diffusion data, shape prior information, and roughness penalty. The dissertation first describes and demonstrates the proposed method on the 2D dataset and then extends it to 3D Phantom data and the real brain data. The results show that the proposed method is relatively immune to issues such as noise, complicated fiber structure like fiber crossings and kissing, false positive fibers, and achieve more explainable tractography results. / A Dissertation submitted to the Department of Statistics in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Spring Semester 2019. / April 16, 2019. / active contours, Bayesian estimation, dMRI fiber tracts, geometric shape analysis, tractography / Includes bibliographical references. / Anuj Srivastava, Professor Directing Dissertation; Eric Klassen, University Representative; Wei Wu, Committee Member; Fred Huffer, Committee Member.

Thesis (Ph. D.)--University of Chicago, Dept. of Radiology, June 1997. / Includes bibliographical references. Also available on the Internet.

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Thesis (Ph.D.)--University of Western Australia, 2004.

Thesis (M.S.)--Rochester Institute of Technology, 1982. / Typescript. Includes bibliographical references (leaves 87-89).