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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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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