Browsing by Author "Alshahrani, Mohammed"

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DEEP LEARNING APPROACHES FOR OBJECT TRACKING AND MOTION ESTIMATION OF ULTRASOUND IMAGING SEQUENCES
(Saudi Digital Library, 2023) Alshahrani, Mohammed; Almekkawy, Mohamed
In recent decades, object tracking and motion estimation in medical imaging have gained importance. It is a powerful tool that can be used to improve diagnostic accuracy and therapy efficiency. This importance has led researchers to search for faster and more accurate algorithms for object tracking. Different approaches have been used to perform object tracking, such as object detection, motion estimation, and similarity matching, which are the focus of this study. Different avenues can be used to address similarity matching. First, the classical method, which takes an object and searches for a similar object in the subsequent frame (because it is an object tracking in a video sequence) by examining all the sub-windows in the subsequent frame and measuring a cost function between the reference object and the sub-window. This approach is inefficient and cannot achieve real-time tracking. The deep learning method for similarity matching utilizes twin convolutional networks that produce a feature map that is later combined using a correlation layer. This layer provides a score map that points to a high-similarity area. This study examined and developed object tracking algorithms to track objects of interest in the human liver using a correlation filter-based neural network (CFNet). The dataset used in this study was CLUST-2D, which was provided by the Swiss Federal Institute of Technology in Zürich (ETH). It contains approximately 96 ultrasound sequences of the liver from different patients. Three versions of the CFNet network were tested in this study. First, baseline-CFNet was used for training. Baseline-CFNet struggled to track objects under significant displacements and deformations. To address this limitation of the baseline-CFNet, a second version was developed. Advanced-CFNet is the second version of CFNet implemented in this study. This is the main contribution of this study. This version incorporates a dynamic template update and motion prediction modules, which improve object tracking by preventing tracker drift and maintaining the template from being polluted with inappropriate appearances of the tracked object. The third version implemented in this study is Kalman-CFNet, which utilizes a linear Kalman filter to estimate an object's motion and enhance its robustness against unexpected motions. The comparative analysis demonstrated the superiority of Advanced-CFNet, as it achieved lower root mean square error (RMSE) values than the other methods, particularly in challenging scenarios. These findings highlight the effectiveness of the advanced CFNet for object tracking in liver ultrasound imaging.
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Essays in Labor Economics: Licensing Policy, Export–Productivity Dynamics, and Shifts Among Remote-Work Managers
(Saudi Digital Library, 2025) Alshahrani, Mohammed; Papazyan, Freddie
This dissertation combines three empirical studies in labor economics, employing both micro- and macro-level analyses. The studies address important issues related to occupational licensing, export structure and labor productivity, and remote work among managers, each using real-world data and econometric methods to answer relevant research questions. The first study examines the impact of the Enhanced Nurse Licensure Compact (eNLC) on the labor market outcomes of registered nurses (RNs) and licensed practical/vocational nurses (LPN/VNs) in five newly participating states. Using monthly data from the Current Population Survey (CPS) between January 2016 and February 2020, the study applies a Difference-in-Differences (DiD) model. The results show that nurses in the newly compact states experienced a 3.6% reduction in real hourly wages after the policy, while the likelihood of working full-time increased by 23.7%. Usual weekly hours showed no significant change. These findings suggest that the eNLC may improve job access while influencing wage dynamics among the biggest licensed group in the healthcare industry. The second study investigates how trade openness and the composition of exports and imports affect labor productivity in resource-intensive countries. Using annual panel data for 15 countries from 2005 to 2019 and a Panel Vector Autoregression (PVAR) model, the analysis compares very high HDI countries with high/medium HDI countries. In very high HDI countries, trade openness and natural resource exports support labor productivity growth, while higher productivity also leads to stronger trade engagement. In contrast, high/medium HDI countries show weaker or negative effects from resource exports and trade openness, with only manufacturing imports having a delayed positive effect. These results highlight how institutional strength and economic structure influence the gains from natural resource exports. The third study analyzes how the COVID-19 pandemic influenced the labor market outcomes of remote working managers. Using annual data from the American Community Survey (ACS) from 2017 to 2023 (excluding 2020) and applying a Regression Discontinuity in Time (RDiT) design, the study focuses on real hourly wages, weekly hours, and full-time employment. The results show that hourly wages increased by 7%, hours worked rose by 3%, and the probability of full-time employment went up by nearly five percentage points. These patterns are consistent across demographic groups and confirm that remote work has become a permanent feature of the labor market for high-skilled managerial workers. Together, these studies provide timely evidence on how labor markets respond to changes in policy, trade, and work structure, offering insights for researchers, policymakers, and institutions shaping the future of work.
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Exercise and quality of life in patients with alpha-1 antitrypsin deficiency
(Saudi Digital Library, 2023-12-04) Alshahrani, Mohammed; Pye, Anita; Turner, Alice
Introduction Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder that affects the production of a protein called alpha-1 antitrypsin. This protein helps to protect the lungs from damage. People with AATD are at increased risk of developing lung and liver diseases. This dissertation explores the effectiveness of exercise on the quality of life in AATD patients. Physical activity is known to have many health benefits, including improving lung function, and reducing the risk of chronic diseases. However, it is not clear whether physical activity is beneficial for people with AATD. The main aim of this study is to examine the relationship between exercise and quality of life in AATD patients who lead physically active or sedentary lifestyles. Methods This cross-sectional study examined the associations between physical activity, quality of life, and well-being in 64 participants with AATD. Utilising a customised questionnaire, activity levels and perspectives were evaluated. More clinical information was extracted from the AATD registry. Results There were 64 participants whose ages and lung function varied considerably. Perspectives on physical activity varied; some were physically active while others were sedentary. The impact of AATD on activity capacity varied among participants. The majority of respondents reported that physical activity improves Quality of life (QOL) and emotional health, but some described barriers. Diverse forms of exercise were preferable. Patients who engaged in more physical activity reported improved quality of life, including less shortness of breath, fatigue, and anxiety, according to the results. In addition, they reported having higher levels of energy and generally feeling better. Positive correlations were observed between physical activity, QOL, and emotional well-being. Conclusion These findings suggest that physical activity would be a beneficial intervention for AATD patients. in addition, this dissertation highlights the importance of incorporating exercise as an integral component of holistic health management for individuals with AATD, showcasing its potential to improve various dimensions of quality of life, both physically and emotionally. However, more research is needed to confirm these findings and to determine the optimal amount and type of physical activity for AATD patients with larger sample size.
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