Engineering Commons^™

Deep Reinforcement Learning In Medical Object Detection And Segmentation, Dong Zhang

Electronic Thesis and Dissertation Repository

Medical object detection and segmentation are crucial pre-processing steps in the clinical workflow for diagnosis and therapy planning. Although deep learning methods have achieved considerable performance in this field, they impose several shortcomings, such as computational limitations, sub-optimal parameter optimization, and weak generalization. Deep reinforcement learning as the newest artificial intelligence algorithm has great potential to address the limitation of traditional deep learning methods, as well as obtaining accurate detection and segmentation results. Deep reinforcement learning has a cognitive-like process to propose the area of desirable objects, thereby facilitating accurate object detection and segmentation. In this thesis, we deploy deep …

A Simple, Realistic Walled Phantom For Intravascular And Intracardiac Applications., Hareem Nisar, John Moore, Roberta Piazza, Efthymios Maneas, Elvis C S Chen, Terry M Peters

Robarts Imaging Publications

PURPOSE: This work aims to develop a simple, anatomically and haptically realistic vascular phantom, compatible with intravascular and intracardiac ultrasound. The low-cost, dual-layered phantom bridges the gap between traditional wall-only and wall-less phantoms by showing both the vessel wall and surrounding tissue in ultrasound imaging. This phantom can better assist clinical tool training, testing of intravascular devices, blood flow studies, and validation of algorithms for intravascular and intracardiac surgical systems.

METHODS: Polyvinyl alcohol cryogel (PVA-c) incorporating a scattering agent was used to obtain vessel and tissue-mimicking materials. Our specific design targeted the inferior vena cava and renal bifurcations which were …

Simulation Approaches To X-Ray C-Arm-Based Interventions, Daniel R. Allen

Electronic Thesis and Dissertation Repository

Mobile C-Arm systems have enabled interventional spine procedures, such as facet joint injections, to be performed minimally-invasively under X-ray or fluoroscopy guidance. The downside to these procedures is the radiation exposure the patient and medical staff are subject to, which can vary greatly depending on the procedure as well as the skill and experience of the team. Standard training methods for these procedures involve the use of a physical C-Arm with real X-rays training on either cadavers or via an apprenticeship-based program. Many guidance systems have been proposed in the literature which aim to reduce the amount of radiation exposure …

A 3d Printed Axon-Mimetic Diffusion Mri Phantom, Tristan K. Kuehn

Electronic Thesis and Dissertation Repository

Diffusion MRI is used to non-invasively characterize the microstructure of the brain. However, the accuracy of the characterization is difficult to verify because no other non-invasive imaging modality provides the same information. This thesis presents a novel 3D printed axon-mimetic (3AM) diffusion MRI phantom, a synthetic object designed to mimic the brain's microstructure.

The phantoms were characterized using microscopy, synchrotron micro-computed tomography, and diffusion MRI, and found to have sufficiently axon-mimetic properties to be useful as diffusion MRI phantoms. A set of phantoms designed to have anatomically realistic and complex fibre structures was used to test the response of diffusion …

Detecting Command-Driven Brain Activity In Patients With Disorders Of Consciousness Using Tr-Fnirs, Androu Abdalmalak

Electronic Thesis and Dissertation Repository

Vegetative state (VS) is a disorder of consciousness often referred to as “wakefulness without awareness”. Patients in this condition experience normal sleep-wake cycles, but lack all awareness of themselves and their surroundings. Clinically, assessing consciousness relies on behavioural tests to determine a patient’s ability to follow commands. This subjective approach often leads to a high rate of misdiagnosis (~40%) where patients who retain residual awareness are misdiagnosed as being in a VS. Recently, functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI), has allowed researchers to use command-driven brain activity to infer consciousness. Although promising, the cost and accessibility …

Video Processing For The Evaluation Of Vascular Dynamics In Neurovascular Interventions, Reid Vassallo

Electronic Thesis and Dissertation Repository

An arteriovenous malformation (AVM) is an abnormal collection of blood vessels which causes blood to travel from arteries to veins through an abnormal twisted network of vessels. This network has an elevated risk of rupture, which can lead to permanent disability and death if the rupture occurs in the brain. The gold standard treatment for AVM is surgical resection, and it is crucial to know which vessels are bringing blood towards and away from the AVM. Unfortunately, it is almost impossible to know this by looking at the surgical scene. The primary limitations of current methods to address this are …

Pulmonary Imaging Of Chronic Obstructive Pulmonary Disease Using Multi-Parametric Response Maps, Jonathan Macneil

Electronic Thesis and Dissertation Repository

Chronic obstructive pulmonary disease (COPD) is characterized by irreversible airflow obstruction caused by airway remodelling and parenchymal destruction. Clinically, observation of COPD is performed using spirometry, but this technique only provides a global measure of lung health. To supplement these clinical measurements, thoracic computed tomography (CT) and hyperpolarized gas magnetic resonance imaging (MRI) have been used to measure regional structure and function abnormalities. Although CT and MRI have been used to research COPD, combination of both modalities into an interrelated image has never been performed. Therefore, we developed an image processing pipeline to combine MRI-CT information into a multi-parametric response …