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Medical image analysis using computer-based algorithms has attracted considerable attention from the research community and achieved tremendous progress in the last decade. With recent advances in computing resources and availability of…
Developing high-performance cathode materials for magnesium-ion batteries (MIBs) remains challenging because Mg$^{2+}$ ions move slowly, and conventional materials exhibit low voltage outputs. In this study, machine learning and…
Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consisting of measurement data and ground-truth images. However,…
Breast X-ray CT imaging is being considered in screening as an extension to mammography. As a large fraction of the population will be exposed to radiation, low-dose imaging is essential. Iterative image reconstruction based on solving an…
Purpose: To experimentally validate the Fastcat cone beam CT (CBCT) simulator against kV and MV CBCT images acquired with a Varian Truebeam linac. Methods: kV and MV CBCT images of a Catphan 504 phantom were acquired using a 100 kVp beam…
The magnetic compression experiment at General Fusion was a repetitive non-destructive test to study plasma physics to Magnetic Target Fusion compression. A compact torus (CT) is formed with a co-axial gun into a containment region with an…
We present results from a detailed GEANT4 simulation of a proposed Muon Tomography System that employs compact Micro Pattern Gas Detectors with high spatial resolution. A basic Point-Of-Closest-Approach algorithm is applied to reconstructed…
Proton Computed Tomography (pCT) provides a promising solution to enhance the accuracy of Relative Stopping Power (RSP) required for proton therapy planning. This research introduces a novel high-granularity pCT architecture that…
Tomographic imaging techniques using the Coulomb scattering of cosmic-ray muons have been shown previously to successfully identify and characterise low- and high-Z materials within an air matrix using a prototype scintillating-fibre…
Deep neural networks have received considerable attention in clinical imaging, particularly with respect to the reduction of radiation risk. Lowering the radiation dose by reducing the photon flux inevitably results in the degradation of…
Purpose: Photon-counting computed tomography (PCCT) shows promise for medical imaging in regards to material separation and imaging of multiple contrast agents. However, many PCCT setups are under development and are not optimized for…
Purpose: To evaluate the cumulative radiobiological impact of daily Megavoltage Cone-Beam Computed Tomography (MV-CBCT) imaging dose based on Normal Tissue Complication Probability (NTCP) and Excess Absolute Risk (EAR) of secondary…
We describe initial results of our program to develop and test Cd-Zn-Te (CZT) detectors with a pixellated array readout. Our primary interest is in the development of relatively thick CZT detectors for use in astrophysical coded aperture…
Automated medical image classification with convolutional neural networks (CNNs) has great potential to impact healthcare, particularly in resource-constrained healthcare systems where fewer trained radiologists are available. However,…
Metal artifacts in computed tomography (CT) arise from a mismatch between physics of image formation and idealized assumptions during tomographic reconstruction. These artifacts are particularly strong around metal implants, inhibiting…
Positron Emission Tomography (PET) and Computed Tomography (CT) are essential for diagnosing, staging, and monitoring various diseases, particularly cancer. Despite their importance, the use of PET/CT systems is limited by the necessity for…
We introduce an ultrahigh-resolution (50\mu m\) robotic micro-CT design for localized imaging of carotid plaques using robotic arms, cutting-edge detector, and machine learning technologies. To combat geometric error-induced artifacts in…
This study investigates the use of High-Performance Computing (HPC) to simulate flow and transport in ultra-large micro-CT images of porous materials using Computational Fluid Dynamics (CFD). Two distinct rock samples, representative of two…
We are exploring low-dose proton radiography and computed tomography (pCT) as techniques to improve the accuracy of proton treatment planning and to provide artifact-free images for verification and adaptive therapy at the time of…
Accurately assessing the risk of cesarean section (CS) delivery is critical, especially in settings with limited medical resources, where access to healthcare is often restricted. Early and reliable risk prediction allows better-informed…