Efficient Cone Beam Reconstruction For The Distorted Circle And Line Trajectory

We propose an exact filtered backprojection algorithm for inversion of the cone beam data in the case when the trajectory is composed of a distorted circle and a line segment. The length of the scan is determined by the region of interest , and it is independent of the size of the object. With few geometric restrictions on the curve, we show that we have an exact reconstruction. Numerical experiments demonstrate good image quality

IMPROVED IMAGE QUALITY IN CONE-BEAM COMPUTED TOMOGRAPHY FOR IMAGE-GUIDED INTERVENTIONS

In the past few decades, cone-beam computed tomography (CBCT) emerged as a rapidly developing imaging modality that provides single rotation 3D volumetric reconstruction with sub-millimeter spatial resolution. Compared to the conventional multi-detector CT (MDCT), CBCT exhibited a number of characteristics that are well suited to applications in image-guided interventions, including improved mechanical simplicity, higher portability, and lower cost. Although the current generation of CBCT has shown strong promise for high-resolution and high-contrast imaging (e.g., visualization of bone structures and surgical instrumentation), it is often believed that CBCT yields inferior contrast resolution compared to MDCT and is not suitable for soft-tissue imaging. Aiming at expanding the utility of CBCT in image-guided interventions, this dissertation concerns the development of advanced imaging systems and algorithms to tackle the challenges of soft-tissue contrast resolution. The presented material includes work encompassing: (i) a comprehensive simulation platform to generate realistic CBCT projections (e.g., as training data for deep learning approaches); (ii) a new projection domain statistical noise model to improve the noise-resolution tradeoff in model-based iterative reconstruction (MBIR); (iii) a novel method to avoid CBCT metal artifacts by optimization of the source-detector orbit; (iv) an integrated software pipeline to correct various forms of CBCT artifacts (i.e., lag, glare, scatter, beam hardening, patient motion, and truncation); (v) a new 3D reconstruction method that only reconstructs the difference image from the image prior for use in CBCT neuro-angiography; and (vi) a novel method for 3D image reconstruction (DL-Recon) that combines deep learning (DL)-based image synthesis network with physics-based models based on Bayesian estimation of the statical uncertainty of the neural network. Specific clinical challenges were investigated in monitoring patients in the neurological critical care unit (NCCU) and advancing intraoperative soft-tissue imaging capability in image-guided spinal and intracranial neurosurgery. The results show that the methods proposed in this work substantially improved soft-tissue contrast in CBCT. The thesis demonstrates that advanced imaging approaches based on accurate system models, novel artifact reduction methods, and emerging 3D image reconstruction algorithms can effectively tackle current challenges in soft-tissue contrast resolution and expand the application of CBCT in image-guided interventions

Techniques and applications for preclinical SPECT

Two developments of the past decade have spurred the development of SPECT as a useful tool for preclinical research. Development of the pinhole collimator, and the growing library of imaging probes for use with SPECT beyond the traditional markers for perfusion or tumor metabolism have both increased the potential uses of SPECT for small animal research. The oblique geometry of pinhole rays originating toward the edges of the FOV results in incomplete sampling and poor image quality away from the pinhole orbit plane. Correction requires an orbit that includes an axial component of motion. A simple solution was developed by placing circular orbits at multiple axial locations along the length of the object. When reconstructed with an OSEM algorithm, the multiple projection sets improved data completeness and reconstructed image quality for simulated and experimental data. Pinhole collimators provide the greatest resolution and highest sensitivity when the object distance is minimized. In actuality, objects are placed some distance from the aperture to ensure that the camera field-of-view is large enough to avoid truncation. A method for improvement was tested by decreasing object distance and obtaining multiple offset projection sets. The two truncated projection sets were then be reconstructed with OSEM to create an image at with improved resolution. In addition to advancements in acquisition strategies, the work in this dissertation details two preclinical projects using the microSPECT camera. The microSPECT camera was used to examine the biodistribution of labeled monoclonal and polyclonal antibodies against the neutrophil protein myeloperoxidase. Mice injected with Staph-A were imaged at 24hr post infection with increased uptake of the tracer probe witnessed in the infected region. A second application required the measurement of hematocrit values using SPECT and labeled erythrocytes and plasma with 99mTc in ischemic rats. SPECT imaging of the labeled plasma and RBCs showed increases in hematocrit values within the ischemic lesion as defined from an HMPAO perfusion image. Moreover, the hematocrit value varied inversely with the perfusion deficit. For regions of poor blood flow, hematocrit was higher. During reperfusion, when flow was restored, or increased above normal levels, hematocrit levels dropped

Towards improving detection rates of gravitational waves from precessing binary black holes

According to Einstein’s theory of General Relativity, the acceleration of matter can cause ripples in the curvature of spacetime, given the name gravitational waves. Such ripples are negligible in magnitude for all but the most energetic astrophysical events, such as the coalescence of compact binary stars. In 2015, gravitational waves were first directly detected from a binary black hole (BBH) coalescence [19]. This was achieved using two independent laser interferometers which each measured the fluctuations caused by the gravitational waves as they passed by. Matched filtering and other data analysis techniques were then employed to identify the properties of the source and measure the likelihood that the detection is a false alarm. The efficacy of these matched filtering techniques is pivotal to not only detecting gravitational waves, but drawing as much information about their sources as possible. The methods for detecting a BBH involve the construction of a template bank; a group of synthesised waveforms which each represent a detectable series of gravitational waves that a BBH could produce. The characteristics of a BBH template are governed by the two masses and how they spin, the distance to the source, its orientation and its sky location. Current template banks do not include templates for sources where the spins are misaligned with the orbital momentum, which is the cause of precession in BBH. Thus, the algorithms are effective for detecting a non-precessing BBH, but much less sensitive towards precessing sources. Creating a template bank which includes all possible precessing waveforms is computationally infeasible and would induce enough statistical noise to negate any extra sensitivity gained. However, many precessing signals would be undetectable or indistinguishable from non-precessing signals. Including such signals in a bank would result in no gain in its sensitivity. This thesis attempts to locate areas of precessing parameter space where waveforms are distinguishable from non-precessing sources, and begins work on forming a function which maps observable precession through parameter space.

Strategy for an initial Measurement of the Inclusive Jet Cross Section with the CMS Detector

A strategy for an initial measurement of the inclusive jet cross section is presented and the related dominating systematic uncertainties are discussed. The study of this observable allows a fundamental probe of the theory of the strong interaction at unpreceeded energies. Additionally a method is presented to compare these measurements to calculations performed at next-to-leading order precision. In this context the dominating theoretical uncertainties are compared to the experimental ones

NASA Tech Briefs, July 1992

Topics include: New Product Ideas; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences

High-quality computed tomography using advanced model-based iterative reconstruction

Computed Tomography (CT) is an essential technology for the treatment, diagnosis, and study of disease, providing detailed three-dimensional images of patient anatomy. While CT image quality and resolution has improved in recent years, many clinical tasks require visualization and study of structures beyond current system capabilities. Model-Based Iterative Reconstruction (MBIR) techniques offer improved image quality over traditional methods by incorporating more accurate models of the imaging physics. In this work, we seek to improve image quality by including high-fidelity models of CT physics in a MBIR framework. Specifically, we measure and model spectral effects, scintillator blur, focal-spot blur, and gantry motion blur, paying particular attention to shift-variant blur properties and noise correlations. We derive a novel MBIR framework that is capable of modeling a wide range of physical effects, and use this framework with the physical models to reconstruct data from various systems. Physical models of varying degrees of accuracy are compared with each other and more traditional techniques. Image quality is assessed with a variety of metrics, including bias, noise, and edge-response, as well as task specific metrics such as segmentation quality and material density accuracy. These results show that improving the model accuracy generally improves image quality, as the measured data is used more efficiently. For example, modeling focal-spot blur, scintillator blur, and noise iicorrelations enables more accurate trabecular bone visualization and trabecular thickness calculation as compared to methods that ignore blur or model blur but ignore noise correlations. Additionally, MBIR with advanced modeling typically outperforms traditional methods, either with more accurate reconstructions or by including physical effects that cannot otherwise be modeled, such as shift-variant focal-spot blur. This work provides a means to produce high-quality and high-resolution CT reconstructions for a wide variety of systems with different hardware and geometries, providing new tradeoffs in system design, enabling new applications in CT, and ultimately improving patient care

Image Quality, Modeling, and Design for High-Performance Cone-Beam CT of the Head

Diagnosis and treatment of neurological and otolaryngological diseases rely heavily on visualization of fine, subtle anatomical structures in the head. In particular, high-quality head imaging at the point of care mitigates patient risk associated with transport and decreases time to diagnosis for time-sensitive diseases. Cone-beam computed tomography (CBCT) systems have found widespread adoption in diagnostic and image-guided procedures. Such systems exhibit potential for adaptation as point-of-care systems due to relatively low cost, mechanical simplicity, and inherently high spatial resolution, but are generally challenged by low contrast imaging tasks (e.g., visualization of tumors or hemorrhages). This thesis details the development and design of a CBCT imaging system with performance sufficient for high-quality imaging of the head and suitable to deployment at the point of care. The performance of a commercially available head-and-neck CBCT scanner was assessed to determine the potential of such systems for high-quality head imaging. Results indicated low-contrast visualization was challenged by high detector noise and scatter. Photon counting x-ray detectors (PCDs) were identified as a potential technology that could improve the low-contrast visualization, and an imaging performance model was developed to quantify their imaging performance. The model revealed important implications for energy resolution, noise, and spatial resolution as a function of energy threshold and charge sharing rejection. A new CBCT system dedicated to detection of low-contrast contrast intracranial hemorrhage was designed with guidance from an imaging chain model to optimize the system configuration (geometry, detector, x-ray source, etc.). The results indicated flat panel detectors (FPDs) were favorable due to a large field of view, but benefited from detector readout gain adjustments. Dual-gain detector readout was compared with use of bowtie filter in high-gain readout mode to investigate potential improvements to noise performance in FPDs. Finally, technical assessment of the prototype CBCT head scanner (with design based on guidance from the image quality model) indicated performance suitable for translation to clinical studies in the neurosciences critical care unit