Rigid and non-rigid point-based medical image registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Understanding the relationship between the Talented Twenty program and college aspirations for high ranking students at a high priority school

Percentage plans such as the Talented Twenty program purport to assist and motivate high ranking students to attend college and grant access to higher education. This type of plan is particularly important to students enrolled in high priority schools who might not view themselves as potential college students. This study examined the relationship between Florida’s Talented Twenty program that begins intervention with juniors and the college aspirations for high ranking students at a high priority school. Numerous studies have established that increased levels of education lead to higher salaries, career mobility, and an increased quality of life (e.g., Bowen, 1997; Leslie & Brinkman 1988; Pascarella & Terenzini, 1991, Swail, 2000). Given the importance of students’ decisions regarding whether or not they will attend college, understanding how and when they make decisions about attending college is important for them, their parents, advisors, and educational administrators. This research examined students’ perceptions and insights via interviews. The overarching research question was: How do high ranking high school students attending a high priority school in a south Florida district perceive their college opportunities? Sixteen high ranking students, grades nine – 12 from a high priority school in Miami-Dade County participated in the study. Participants were identified by a school counselor and individual semi structured interviews were conducted at the school. Utilizing a student development theoretical framework developed by Hossler and Gallagher (1987) that centered on students’ predisposition, search strategies and choices, data were organized and emergent themes analyzed. The analysis of the data revealed that in alignment with the framework (a) parents were the strongest influence in the development of these students’ college aspirations, (b) these students formalized their higher education plans between eighth and 10th grade, (c) these students actively engaged in academic searches and learning opportunities that increased their chances to be admitted into college, and (d) there was no relationship between knowledge regarding the Talented Twenty program and their educational decisions. This study’s findings suggest that interventions and programs intended to influence the educational aspirations of students are more likely to succeed if they take place by the eighth or ninth grade.

Rigid and Non-rigid Point-based Medical Image Registration

The primary goal of this dissertation is to develop point-based rigid and non-rigid image registration methods that have better accuracy than existing methods. We first present point-based PoIRe, which provides the framework for point-based global rigid registrations. It allows a choice of different search strategies including (a) branch-and-bound, (b) probabilistic hill-climbing, and (c) a novel hybrid method that takes advantage of the best characteristics of the other two methods. We use a robust similarity measure that is insensitive to noise, which is often introduced during feature extraction. We show the robustness of PoIRe using it to register images obtained with an electronic portal imaging device (EPID), which have large amounts of scatter and low contrast. To evaluate PoIRe we used (a) simulated images and (b) images with fiducial markers; PoIRe was extensively tested with 2D EPID images and images generated by 3D Computer Tomography (CT) and Magnetic Resonance (MR) images. PoIRe was also evaluated using benchmark data sets from the blind retrospective evaluation project (RIRE). We show that PoIRe is better than existing methods such as Iterative Closest Point (ICP) and methods based on mutual information. We also present a novel point-based local non-rigid shape registration algorithm. We extend the robust similarity measure used in PoIRe to non-rigid registrations adapting it to a free form deformation (FFD) model and making it robust to local minima, which is a drawback common to existing non-rigid point-based methods. For non-rigid registrations we show that it performs better than existing methods and that is less sensitive to starting conditions. We test our non-rigid registration method using available benchmark data sets for shape registration. Finally, we also explore the extraction of features invariant to changes in perspective and illumination, and explore how they can help improve the accuracy of multi-modal registration. For multimodal registration of EPID-DRR images we present a method based on a local descriptor defined by a vector of complex responses to a circular Gabor filter.

Best Practices: Lessons Learned by a South Florida Non-Profit Community Based Organization while Designing and Implementing a Career Exploration Evidence Informed Framework in Urban Communities

All A’s was designed to support of the agency’s family strengthening initiatives in South Florida. All A’s uses evidence informed strategies poised to be an inclusive curriculum that teaches self-determination and adaptive behavior skills. The framework incorporates problem based learning and adult learning theory and follows the Universal Design for Learning. Since 2012, the agency has served over 8500 youth and 4,000 adults using the framework. The framework addresses educational underachievement and career readiness in at risk populations. It is used to enhance participants AWARENESS of setting SMART goals to achieve future goals and career aspirations. Participants are provided with ACCESS to resources and opportunities for creating and implementing an ACTION plan as they pursue and ACHIEVE their goals. All A’s promotes protective factors and expose youth to career pathways in Science, Technology, Engineering and Math (STEM) related fields. Youth participate in college tours, job site visits, job shadowing, high school visits, online college and career preparation assistance, service learning projects, STEM projects, and the Winning Futures© mentoring program. Adults are assisted with résumé development; learn job search strategies, interview techniques, job shadowing experiences, computer and financial literacy programs. Adults and youth are also given the opportunity to complete industry-recognized certifications in high demand industries (food service, general labor, and construction), and test preparation for the General Educational Development Test.

Genetic algorithms and investment strategies: A global perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: (1) help global investors determine the optimal selection and holding periods for momentum portfolios, (2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, (3) assess the investment strategy profits after considering transaction costs, and (4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.

Genetic Algorithms and Investment Strategies: A Global Perspective

The profitability of momentum portfolios in the equity markets is derived from the continuation of stock returns over medium time horizons. The empirical evidence of momentum, however, is significantly different across markets around the world. The purpose of this dissertation is to: 1) help global investors determine the optimal selection and holding periods for momentum portfolios, 2) evaluate the profitability of the optimized momentum portfolios in different time periods and market states, 3) assess the investment strategy profits after considering transaction costs, and 4) interpret momentum returns within the framework of prior studies on investors’ behavior. Improving on the traditional practice of selecting arbitrary selection and holding periods, a genetic algorithm (GA) is employed. The GA performs a thorough and structured search to capture the return continuations and reversals patterns of momentum portfolios. Three portfolio formation methods are used: price momentum, earnings momentum, and earnings and price momentum and a non-linear optimization procedure (GA). The focus is on common equity of the U.S. and a select number of countries, including Australia, France, Germany, Japan, the Netherlands, Sweden, Switzerland and the United Kingdom. The findings suggest that the evolutionary algorithm increases the annualized profits of the U.S. momentum portfolios. However, the difference in mean returns is statistically significant only in certain cases. In addition, after considering transaction costs, both price and earnings and price momentum portfolios do not appear to generate abnormal returns. Positive risk-adjusted returns net of trading costs are documented solely during “up” markets for a portfolio long in prior winners only. The results on the international momentum effects indicate that the GA improves the momentum returns by 2 to 5% on an annual basis. In addition, the relation between momentum returns and exchange rate appreciation/depreciation is examined. The currency appreciation does not appear to influence significantly momentum profits. Further, the influence of the market state on momentum returns is not uniform across the countries considered. The implications of the above findings are discussed with a focus on the practical aspects of momentum investing, both in the U.S. and globally.