Biomedical Commons^™

A Parallel Fuzzy Logic Framework For Surgical Skill Evaluation Via Instance Segmentation And Deepsort Tracking, Mohsen M. Mohaidat

Dissertations

Manual evaluation of suturing skills during laparoscopic training is often subjective and labor-intensive, resulting in the lack of scalable and consistent feedback for trainees. This study proposes an automated framework that not only significantly reduces the need for in-person assessment by experts but also ensures scalability, thereby addressing the objectivity and cost-effectiveness limitations. While low-cost laparoscopic box trainers have become increasingly popular for residency training, performance assessment still depends on expert supervision. The proposed system aims to alleviate these limitations.

This study introduces a novel automated framework incorporating an optimized DeepSORT algorithm for classifying, localizing, and tracking surgical tools using …

The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine

Dissertations

Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.

This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …

3d Automated Surgeon’S Hand Motion Assessment Using A Cascade Fuzzy Supervisor During Intelligent Box-Trainer System Skills Training In A Multi-Thread Video Processing, Fatemeh Rashidi Fathabadi

Dissertations

For certain surgical procedures, Minimally Invasive Surgery (MIS) has become more advantageous than traditional open surgery. Therefore, mastery of laparoscopic skills is an essential component of surgical training and requires considerable time and effort. The Fundamentals of Laparoscopic Surgery (FLS) program has been developed as a tool to improve and assess fundamental surgical skills. In fact, using a low-cost Box-Trainer or a simulator, laparoscopic surgeons are required to train using a set of structured tasks that can be objectively used to assess their laparoscopic skills, which must be mastered before carrying out real-life laparoscopic procedures. These tasks include peg transfer, …

Towards Reliable Hepatocytic Anatomy Segmentation In Laparoscopic Cholecystectomy Using U-Net With Auto-Encoder, Koloud Najem Alkhamaiseh

Dissertations

Despite the advantages of minimally invasive surgeries that depend heavily on vision, the indirect access and lack of the 3D field of view of the area of interest introduce some complications in the desired procedures. Fortunately, the recorded videos from these procedures offer the opportunity for intra-operative and post-operative analyses, to improve future performance and safety.

Deep learning models for surgical video analysis could therefore support visual tasks such as identifying the critical view of safety (CVS) in laparoscopic cholecystectomy (LC), potentially contributing to the reduction of the current rates of bile duct injuries in LC. Most bile duct injuries …

Improving The Performance And Evaluation Of Computer-Assisted Semen Analysis, Ji-Won Choi

Dissertations

Semen analysis is performed routinely in fertility clinics to analyze the quality of semen and sperm cells of male patients. The analysis is typically performed by trained technicians or by Computer-Assisted Semen Analysis (CASA) systems. Manual semen analysis performed by technicians is subjective, time-consuming, and laborious, and yet most fertility clinics perform semen analysis in this manner. CASA systems, which are designed to perform the same tasks automatically, have a considerable market share, yet many studies still express concerns about their accuracy and consistency. In this dissertation, the focus is on detection, tracking, and classification of sperm cells in semen …

Assessing Structural And Functional Brain Alterations And Work-Related Fatigue In Non-Hyposmic And Hyposmic Covid-19 Survivors, Rakibul Hafiz

Dissertations

In the year 2019, life began to change at the advent of a global pandemic caused by the novel coronavirus. Mask mandates and mass vaccinations have mitigated the effects significantly, yet cases keep rising with new variants, especially, in densely populated countries, like India. Recent neuroimaging evidence shows the virus can attack the central nervous system (CNS). However, exactly which brain regions undergo structural and functional changes remain largely unknown. Many patients experience 'loss of/reduced sense of smell' (i.e., hyposmic) and an alarming number of survivors develop persistent symptoms ('long-COVID') for several months after initial infection. Fatigue is the most …

Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang

Dissertations

Sensors have been receiving significant attention in the last decade and the demand for sensory systems has increased in recent years due to the rapid growth in the field of artificial intelligence (AI). Sensors can improve people’s awareness by providing them with real-time information on the environment and their immediate health conditions. This dissertation presents the fulfilment of three main projects and focuses on the development of a sensor, a sensory system, and a sensor signal recognition system for AI applications by employing printed electronics, analog circuit design, and digital signal processing techniques.

In the first project, a multi-channel stethograph …

Microglia Induced Neuroinflammation Through The Nlrp3 Inflammasome Following Blast Traumatic Brain Injury, Daniel Younger

Dissertations

The incidence of traumatic brain injury (TBI) among military personnel have been steadily increasing with modern conflicts. A recent RAND report estimated 320,000 service members, totaling 20% of deployed forces, suffer from TBI. However, of this population roughly 60% have not seen a medical professional specifically for TBI. Unlike the civilian population, the primary cause of TBI for active-duty military personnel is blast exposure. Blasts now account for over 70% of all US military casualties in operation Iraqi Freedom (OIF) and Operation enduring freedom (OEF) and are the major cause of TBI. Among many pathological mechanisms associated with blast TBI, …

Surface-Enhanced Raman Detection Of Glucose On Several Novel Substrates For Biosensing Applications, Laila Saad Alqarni

Dissertations

The small normal Raman cross-section of glucose is considered to be a major challenge for its detection by Surface Enhanced Raman Spectroscopy (SERS) for medical applications. These applications include blood glucose level monitoring of diabetic patients and evaluation of patients with other medical conditions, since glucose is a marker for many human diseases. This dissertation focuses on Surface-Enhanced Raman Scattering primarily for the detection of glucose. Some experiments also are carried out for the detection of the corresponding enzyme glucose oxidase that is used in electrochemical glucose sensors and in biofuel cells. This project explores the possibility of utilizing Surface …

Compressive Sensing Framework For Mass Spectrometry Data Analysis, Khalfalla Ahmad Kh. Awedat

Dissertations

Mass Spectrometry (MS) data is ideal for identifying unique bio-signatures of diseases. However, the high dimensionality of MS data hinders any promising MS-based proteomics development. The goal of this dissertation is to develop an accurate classification tool by employing compressive sensing (CS). Not only can CS significantly reduce MS data dimensionality, but it also will allow for full reconstruction of original data. The framework developed in this work is based on using L2 and a mixed L2-L1 norms, allowing an overdetermined system to be resolved. The results show that the L2- based algorithm with regularization terms has a better performance …