Dissertations & Theses
http://hdl.handle.net/10106/25171
2024-03-29T10:58:14ZPURSUIT OF ULTIMATE TOMOGRAPHIC IMAGE QUALITY: FROM CLASSICAL METHODS TO DEEP LEARNING
http://hdl.handle.net/10106/31755
PURSUIT OF ULTIMATE TOMOGRAPHIC IMAGE QUALITY: FROM CLASSICAL METHODS TO DEEP LEARNING
**Please note that the full text is embargoed until 8/1/2025** ABSTRACT: Medical imaging plays a crucial role in modern healthcare, serving as a vital component in the realms of diagnosis and treatment. It encompasses a broad spectrum of techniques and technologies aimed at visualizing the internal structure, physiology and bio-chemical processes inside the human body. Medical imaging has revolutionized medical practice by enabling doctors to diagnose diseases and monitor treatments without resorting to invasive procedures. Computed Tomography (CT) is an important tool of medical imaging. A CT scan employs computer-processed combinations of multiple X-ray images taken from different angles to generate cross-sectional images, providing significantly more detailed structural information compared to 2D X-rays. However, CT relies on ionizing radiation and its image quality can deteriorate due to patient motion and reduced imaging dose. In this work, we aim to improve CT image quality (at lower radiation dose) using advanced methods ranging from traditional modeling to deep learning.
In this work, we first developed a general simultaneous motion estimation and image reconstruction (G-SMEIR) method for 4D cone-beam CT (CBCT) to capture and model lung motion for radiation therapy (Chapter 2). It can overcome the local trapping problem of motion estimation and achieve better 4D CBCT image quality and motion tracking for lung tumors. Secondly, we developed several deep learning methods for CT denoising: cycle generative and adversarial network (CycleGAN) and RecycleGAN for unpaired single low-dose CT image denoising and unpaired low-dose CT image sequences denoising, respectively (Chapter 3), and texture transformer for super-resolution (TTSR) for low-dose CT (Chapter 4). These methods yield unprecedented denoising performance compared to other state-of-the-art denoising methods. This dissertation work not only provides multiple tools to address important issues in CT, but also demonstrates that advanced modeling and deep learning methods are effective in solving challenging problems in medical imaging.
2023-08-15T00:00:00ZTHE EFFECT OF CORPORATE GOVERNANCE ON THE CHANGE IN MARKET VALUATION OF CORPORATE SPIN-OFFS: AN EMPIRICAL INVESTIGATION OF SPUN-OFF SUBSIDIARIES
http://hdl.handle.net/10106/31667
THE EFFECT OF CORPORATE GOVERNANCE ON THE CHANGE IN MARKET VALUATION OF CORPORATE SPIN-OFFS: AN EMPIRICAL INVESTIGATION OF SPUN-OFF SUBSIDIARIES
This dissertation focuses on the change in market valuation of spun-off subsidiaries two years after the corporate spin-off. A review of the literature indicates that the research pertaining to determinants of the market valuation following corporate spin-offs from the perspective of spun-off subsidiaries has been limited. While the extensive corporate governance literature indicates that different governance structures of the firm have diverse implications on the choice of firm strategies and associated performance, our knowledge of how these governance elements might impact the change in market valuation of spun-off subsidiaries is virtually nonexistent. Grounded in agency, resource dependence, and upper echelons theories, this research examines how board characteristics, CEO characteristics, and ownership structures impact the change in market valuation of the spun-off subsidiary (child firm), which is assessed by the change in market value of equity within two years following the corporate separation of the child from its divesting (parent) firm.
The study is based on 138 completed corporate spin-offs undertaken in the U.S. between 2000 and 2014, identified using the SDC Platinum database. My results indicate that the board size and CEO duality have significant positive effects on the change in market valuation of the child firm whereas the CEO age and managerial ownership have significant negative effects on this relationship. On the other side, the board average age, CEO origin, board independence, institutional ownership, and board members’ and CEOs’ external directorships do not show any significant effects on the change in market valuation of the child firm.
Regarding research contributions, this study is grounded in three established theories —agency, resource dependence, and upper echelons — to explain an important phenomenon of the change in market valuation of the child firm following the spin-off. Secondly, the study demonstrates critical effects of the corporate governance structure, including board and CEO characteristics as well as ownership structures on the change in post-spin-off market valuation from the perspective of the child firm. Thirdly, the study uses the market value of equity to assess the market valuation, which provides important cues regarding investor perceptions of the child firm’s business prospects.
Concerning managerial implications, this study indicates that larger boards, younger CEOs, and the CEO and chairman of the board being the same person all help to improve the child firm’s market valuation. On the opposite side, a large number of shares owned by managers will negatively affect the market valuation of the child firm. These results can be considered critical key points for establishing an effective governance structure at the child firm.
EXPLORING THE PREDICTORS OF WELL-BEING AND ADVANCE DIRECTIVES AMONG ELDER ORPHANS: A MIXED METHODS STUDY
http://hdl.handle.net/10106/31664
EXPLORING THE PREDICTORS OF WELL-BEING AND ADVANCE DIRECTIVES AMONG ELDER ORPHANS: A MIXED METHODS STUDY
Elder orphan is a term popularized by the media to describe the more than 22% of community-dwelling US adults aging alone with limited social support, social isolation, multiple chronic health issues, and childlessness. Elder orphans who have not initiated advance directives are at risk of becoming unbefriended, having no able or willing family or friends to make medical decisions during acute injury or medical crisis. The purpose of this explanatory sequential mixed-methods study was to understand the determinants of well-being and advance care planning. A cross-sectional analysis of members (n = 368) of an online Facebook group of elder orphans was conducted followed by an interpretative phenomenological analysis of in-depth interviews with (n = 6) volunteer participants.
Hierarchical regression revealed income, adverse childhood experiences, discrimination, social network, and multiple health issues were found to be significant predictors of well-being among elder orphans, whereas mid-life events were not significant predictors of well-being among elder orphans. Contradictory to prediction, higher levels of well-being increased the likelihood of having advance directives while perceived risk of incapacitation had no influence on the likelihood of having advance directives. The qualitative follow-up interpretative phenomenological analysis revealed four sub-ordinate themes: (1) the road to elder orphanhood: making meaning of the past; (2) a sudden halt: caregiving experiences and consequences; (3) connecting and trying to connect; and (4) barriers and future concerns. This study represents a unique and valuable examination of an under-studied group of older adults, who are often unidentified by health care professionals.
2018-08-20T00:00:00ZACCESS TO OPPORTUNITY AND THE IMPACTS ON HOUSING VALUE
http://hdl.handle.net/10106/27671
ACCESS TO OPPORTUNITY AND THE IMPACTS ON HOUSING VALUE
Accessibility is the well stablished concept in theories of urban planning and spatial structure. This dissertation measured access to opportunities that incorporate major destinations as well as all jobs for three modes. The study used the most updated transportation network to measure access to opportunities by gravity equation that account for distance and mode. It also used Principal Component Analysis to make the opportunity scores out of several related destinations and to make overall score by incorporating all the opportunities.
The developed access to opportunity scores were applied to evaluate the location efficiencies of major affordable housing units in DFW. I found that most of affordable housing units are located in least location efficient places by walking and transit. However, among them, HCV and LIHTC affordable programs presented a better performance than other ones.
The new score was used to determined areas with the high and low access chances for DFW. Based on the analysis for this research, the residents had poor access to opportunities by walking and transit and good access to opportunities by driving. I also used the developed scores to examine the spatial distribution of new development projects in areas of opportunities. I found that most of the projects are happening in areas that have low access to opportunities by walking and transit, but they have good access by car.
Moreover, the relation to housing value is the topic of large volume of the studies. However, currently, there have been some changes in household travel behavior. Households are reported to commute less to access jobs due to the advances in communication and information technologies. In addition, they travel more to access the destinations other than jobs. Moreover, US families showed the demand to use more active mode of transportation such as biking and walking for commuting to work. These new trends might have the reflection on housing value. This study attempted to examine the topic by developing two models to compare the impact of access to job with the impact of access to the destinations other than job. The result of this study showed that housing market is still influenced by job accessibility.
2018-08-13T00:00:00Z