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Articles 1 - 12 of 12
Full-Text Articles in Radiology
A Framework For Digital Energy Modulation And Translation In Projectional X-Ray Imaging, Richard R. Wargo
A Framework For Digital Energy Modulation And Translation In Projectional X-Ray Imaging, Richard R. Wargo
Theses and Dissertations
In projectional X-ray imaging, acquisition energy fundamentally influences subject contrast, image noise, and radiation dose. While dual-energy techniques exploit spectral differences to optimize contrast and enable material separation, acquiring multiple images of the same anatomy often requires additional exposures and increased system complexity.
This dissertation presents a framework for digital energy modulation (DEM), in which computational models are trained to translate projection images between energy domains without requiring additional X-ray acquisitions. DEM is conceived as a generalizable strategy for controlled contrast modulation in projection imaging, with potential applications in image optimization, radiation therapy alignment, and dual-energy applications.
The framework was …
Synthesis Of Photocleavable Molecules For Neurological Applications, Nishal Madujith Egodawaththa Arachchilage Don
Synthesis Of Photocleavable Molecules For Neurological Applications, Nishal Madujith Egodawaththa Arachchilage Don
Theses and Dissertations
In recent biomedical research, the precise control of molecular dynamics through light activation has emerged as a powerful tool, particularly in the field of neurobiology. This approach involves the use of photocleavable cages or photoprotective groups (PPGs) that are chemically tethered to biologically active molecules such as neurotransmitters or calcium chelators. These cages remain inert until exposed to specific wavelengths of light, typically in the visible range, triggering the release of the active compound with high spatiotemporal precision.
For neurotransmitter systems, such as glutamate (Glu), which plays a critical role in synaptic transmission and memory formation, researchers have developed novel …
Cognitive Assessment Of Health-Care Workers Exposed To Ionizing Radiation And The Assessment Of Radiation Safety Awareness In Different Radiation Oncology Hospitals In Egypt, Basma M. Saleh
Theses and Dissertations
The increase in cancer cases and subsequent increase in chemotherapy and radiotherapy sparked worries over hospital workers' health and safety. There is a global trend towards routine assessment of awareness, safety measures, and radiation protection culture among healthcare workers. There is also a trend towards monitoring the various associations between radiation exposure and different health outcomes. In low- and middle-income countries, the use of advanced techniques and biomarker tests to track the health status of the workers is hard to achieve. This is due to the scarce resources and economic instabilities and that is why using a survey as a …
Characterization Of A Solid-State Detector For Dosimetry In The Diagnostic Energy Range With Verification Via Monte Carlo Estimation Of Average Breast Dose In Mammography, Areej Aljabal
Theses and Dissertations
This dissertation aims to develop a simplified QA metric for estimating radiation dose in mammography. This metric, the Mid-Breast Dose (MDB) Index, maybe be proposed as an alternative dose index, consistent with average glandular dose (AGD), for routine QA. MBD was obtained using “Phantom mid-point Air Kerma (AK) measurement” for conventional mammography. The advantage of this method is that MBD can be measured directly without requiring multiple conversion factors. The accuracy of clinical measurements in computing the MBD was assessed by comparing it with the AGD estimated by the Dance formalism experimentally and Monte Carlo simulation.
MBD methodology relies on …
Modeling Of Patient-Specific Periaortic Mechanics And Pulmonary Artery Hemodynamics Based On Phase-Contrast Magnetic Resonance Imaging Sequences., Johane H. Bracamonte
Modeling Of Patient-Specific Periaortic Mechanics And Pulmonary Artery Hemodynamics Based On Phase-Contrast Magnetic Resonance Imaging Sequences., Johane H. Bracamonte
Theses and Dissertations
Inverse modeling in cardiovascular medicine is a collection of methodologies that can provide non-invasive patient-specific estimations of clinical risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs.
Herein, three different phase contrast magnetic resonance imaging (MRI) modalities were implemented as input data, displacement encoding with stimulated echoes (DENSE MRI) applied, and time-resolved velocity encoding phase-contrast MRI, in 1D and 3D, applied to pulmonary artery (PA) hemodynamics.
A model to account for the effect of periaortic interactions due to static and dynamic structures …
A Deep Learning U-Net For Detecting And Segmenting Liver Tumors, Vidhya Cardozo
A Deep Learning U-Net For Detecting And Segmenting Liver Tumors, Vidhya Cardozo
Theses and Dissertations
Visualization of liver tumors on simulation CT scans is challenging even with contrast-enhancement, due to the sensitivity of the contrast enhancement to the timing of the CT acquisition. Image registration to magnetic resonance imaging (MRI) can be helpful for delineation, but differences in patient position, liver shape and volume, and the lack of anatomical landmarks between the two image sets makes the task difficult. This study develops a U-Net based neural network for automated liver and tumor segmentation for purposes of radiotherapy treatment planning. Non-contrast simulation based abdominal CT axial scans of 52 patients with primary liver tumors were utilized. …
Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang
Estimating The Respiratory Lung Motion Model Using Tensor Decomposition On Displacement Vector Field, Kingston Kang
Theses and Dissertations
Modern big data often emerge as tensors. Standard statistical methods are inadequate to deal with datasets of large volume, high dimensionality, and complex structure. Therefore, it is important to develop algorithms such as low-rank tensor decomposition for data compression, dimensionality reduction, and approximation.
With the advancement in technology, high-dimensional images are becoming ubiquitous in the medical field. In lung radiation therapy, the respiratory motion of the lung introduces variabilities during treatment as the tumor inside the lung is moving, which brings challenges to the precise delivery of radiation to the tumor. Several approaches to quantifying this uncertainty propose using a …
Motion-Induced Artifact Mitigation And Image Enhancement Strategies For Four-Dimensional Fan-Beam And Cone-Beam Computed Tomography, Matthew J. Riblett
Motion-Induced Artifact Mitigation And Image Enhancement Strategies For Four-Dimensional Fan-Beam And Cone-Beam Computed Tomography, Matthew J. Riblett
Theses and Dissertations
Four dimensional imaging has become part of the standard of care for diagnosing and treating non-small cell lung cancer. In radiotherapy applications 4D fan-beam computed tomography (4D-CT) and 4D cone-beam computed tomography (4D-CBCT) are two advanced imaging modalities that afford clinical practitioners knowledge of the underlying kinematics and structural dynamics of diseased tissues and provide insight into the effects of regular organ motion and the nature of tissue deformation over time. While these imaging techniques can facilitate the use of more targeted radiotherapies, issues surrounding image quality and accuracy currently limit the utility of these images clinically.
The purpose of …
Advances In Dual-Energy Computed Tomography Imaging Of Radiological Properties, Dong Han
Advances In Dual-Energy Computed Tomography Imaging Of Radiological Properties, Dong Han
Theses and Dissertations
Dual-energy computed tomography (DECT) has shown great potential in the reduction of uncertainties of proton ranges and low energy photon cross section estimation used in radiation therapy planning. The work presented herein investigated three contributions for advancing DECT applications. 1) A linear and separable two-parameter DECT, the basis vector model (BVM) was used to estimate proton stopping power. Compared to other nonlinear two-parameter models in the literature, the BVM model shows a comparable accuracy achieved for typical human tissues. This model outperforms other nonlinear models in estimations of linear attenuation coefficients. This is the first study to clearly illustrate the …
An Investigation Of Nurbs-Based Deformable Image Registration, Travis J. Jacobson
An Investigation Of Nurbs-Based Deformable Image Registration, Travis J. Jacobson
Theses and Dissertations
Deformable image registration (DIR) is an essential tool in medical image processing. It provides a means to combine image datasets, allowing for intra-subject, inter-subject, multi-modality, and multi-instance analysis, as well as motion detection and compensation. One of the most popular DIR algorithms models the displacement vector field (DVF) as B-splines, a sum of piecewise polynomials with coefficients that enable local shape control. B-splines have many advantageous properties in the context of DIR, but they often struggle to adequately model steep local gradients and discontinuities. This dissertation addresses that limitation by proposing the replacement of conventional B-splines with a generalized formulation …
Optimization Of Functional Mri Methods For Olfactory Interventional Studies At 3t, Vishwadeep Ahluwalia
Optimization Of Functional Mri Methods For Olfactory Interventional Studies At 3t, Vishwadeep Ahluwalia
Theses and Dissertations
Functional MRI technique is vital in investigating the effect of an intervention on cortical activation in normal and patient population. In many such investigations, block stimulation paradigms are still the preferred method of inducing brain activation during functional imaging sessions because of the high BOLD response, ease in implementation and subject compliance especially in patient population. However, effect of an intervention can be validly interpreted only after reproducibility of a detectable BOLD response evoked by the stimulation paradigm is first verified in the absence of the intervention. Detecting a large BOLD response that is also reproducible is a difficult task …
Development Of A Mammographic Image Processing Environment Using Matlab, John L. Kelley
Development Of A Mammographic Image Processing Environment Using Matlab, John L. Kelley
Theses and Dissertations
Breast cancer is a disease that accounts for a disturbingly large number of deaths in females each year. Its prevalence is a topic of concern to all of us since it can affect our families, friends, and coworkers. Although mammographic screening is the most effective method currently available for the early detection of breast cancer, it is far from being an infallible procedure. Mammographic reading is error prone, partly because of the complexity of the task and partly because of the variability in human performance. Computers offer high reproducibility, and when used as an adjunct by the radiologist, may improve …