Compressed sensing subtracted rotational angiography with multiple sparse penalty

International audienceDigital Subtraction Rotational Angiography (DSRA) is a clinical protocol that allows three-dimensional (3D) visualization of vasculature during minimally invasive procedures. C-arm systems that are used to generate 3D reconstructions in interventional radiology have limited sampling rate and thus, contrast resolution. To address this particular subsampling problem, we propose a novel iterative reconstruction algorithm based on compressed sensing. To this purpose, we exploit both spatial and temporal sparsity of DSRA. For computational efficiency, we use a proximal implementation that accommodates multiple '1-penalties. Experiments on both simulated and clinical data confirm the relevance of our strategy for reducing subsampling streak artifacts

Compressed Sensing: a new paradigm for Rapid MR Imaging

La teoria del Compressed Sensing si propone di risolvere il problema della ricostruzione di una immagine da un campionamento in frequenza incompleto, sfruttando la proprietà di sparsità di molte immagini. Le immagini da risonanza magnetica (MR) offrono un campo di applicazione a questa teoria, con possibili significativi miglioramenti in termini di tempi di acquisizione e qualità dell'immagin

Limited Angle Ultrasound Tomography of the Compressed Breast

X-ray mammography is widely accepted as the clinical standard for breast cancer screening and diagnosis. However, reflection mode ultrasound has been known to outperform x-ray in screening performance in dense breasts. With newer modes of ultrasound, acoustic properties of breast tissue, such as the speed of sound and attenuation coefficient distributions, can be extracted from captured ultrasound signals and used to characterize breast tissue types and contribute to detection and diagnosis of malignancy. The same is possibly true for optical absorption via photoacoustic imaging. Recently, we have developed a dual-sided ultrasound scanner that can be integrated with existing x-ray mammographic systems and acquire images in the mammographic view and compression. Transmission imaging for speed of sound and attenuation coefficient in this geometry is termed limited angle tomography, as the beams at frequencies yielding high resolution cannot transit the long axis of the compressed breast. This approach, ideally, should facilitate the co-registration and comparisons between images from three modalities discussed here (x-ray, ultrasound and photoacoustic) and increase diagnostic detection confidence. However, potential limitations inherent in limited angle tomography have received minimal exploration up to this study, and existing imaging techniques developed for this approach are based on overly optimistic assumptions that hinder achievement of the desired image quality. This investigation of these problems should contribute valuable information to the validation and translation of the mammographically-configured, dual-sided ultrasound, or ultrasound and photoacoustic, scanner to the clinic. This dissertation first aims to extensively identify possible sources of error resulting from imaging in the limited angle tomography approach. Simulation findings mapping parametric conditions reveal that image artifacts arising in reflection mode (B-mode) can be modulated or mitigated by ultrasound gels with adequate acoustic properties. In addition, sound speed imaging was performed determining the level of significance for several key sources of error. Results suggest that imaging in transmission mode is the most sensitive to transducer misplacement in the signal propagation direction. This misplacement, however, could be minimized easily by routinely calibrating transducer positions. Next, this dissertation aims to advance speed of sound, attenuation, and photoacoustic image reconstruction algorithms for the limited angle tomography approach. This was done by utilizing both structural information of the imaged objects/tissues by means of the corresponding reflection mode images taken from the same imaging location, and a full acoustic modeling framework to account for complex acoustic interactions within the field of view. We have shown through simulations that both a priori information from reflection mode images and full acoustic modeling contribute to a noticeable improvement in the reconstructed images. Work done throughout the course of this dissertation should provide a foundation and insight necessary for improvements upon the existing dual-sided ultrasound scanner towards breast imaging in the clinic.PHDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143944/1/rungroj_1.pd

Experimental characterisation of bubbly flow using MRI

This thesis describes the first application of ultra-fast magnetic resonance imaging (MRI) towards the characterisation of bubbly flow systems. The principle goal of this study is to provide a hydrodynamic characterisation of a model bubble column using drift-flux analysis by supplying experimental closure for those parameters which are considered difficult to measure by conventional means. The system studied consisted of a 31 mm diameter semi-batch bubble column, with 16.68 mM dysprosium chloride solution as the continuous phase. This dopant served the dual purpose of stabilising the system at higher voidages, and enabling the use of ultra-fast MRI by rendering the magnetic susceptibilities of the two phases equivalent. Spiral imaging was selected as the optimal MRI scan protocol for application to bubbly flow on the basis of its high temporal resolution, and robustness to fluid flow and shear. A velocimetric variant of this technique was developed, and demonstrated in application to unsteady, single-phase pipe flow up to a Reynolds number of 12,000. By employing a compressed sensing reconstruction, images were acquired at a rate of 188 fps. Images were then acquired of bubbly flow for the entire range of voidages for which bubbly flow was possible (up to 40.8%). Measurements of bubble size distribution and interfacial area were extracted from these data. Single component velocity fields were also acquired for the entire range of voidages examined. The terminal velocity of single bubbles in the present system was explored in detail with the goal of validating a bubble rise model for use in drift-flux analysis. In order to provide closure to the most sophisticated bubble rise models, a new experimental methodology for quantifying the 3D shape of rising single bubbles was described. When closed using shape information produced using this technique, the theory predicted bubble terminal velocities within 9% error for all bubble sizes examined. Drift-flux analysis was then used to provide a hydrodynamic model for the present system. Good predictions were produced for the voidage at all examined superficial gas velocities (within 5% error), however the transition of the system to slug flow was dramatically overpredicted. This is due to the stabilising influence of the paramagnetic dopant, and reflects that while drift-flux analysis is suitable for predicting liquid holdup in electrolyte stabilised systems, it does not provide an accurate representation of hydrodynamic stability. Finally, velocity encoded spiral imaging was applied to study the dynamics of single bubble wakes. Both freely rising bubbles and bubbles held static in a contraction were examined. Unstable transverse plane vortices were evident in the wake of the static bubble, which were seen to be coupled with both the path deviations and wake shedding of the bubble. These measurements demonstrate the great usefulness for spiral imaging in the study of transient multiphase flow phenomena.This work was supported by the Cambridge Australia Trust and Trinity College, Cambridg

Dictionaries for fast and informative dynamic MRI acquisition

Magnetic resonance (MR) imaging is an invaluable tool for medical research and diagnosis but suffers from inefficiencies. The speed of its acquisition mechanism, based on sequentially probing the interactions between nuclear atom spins and a changing magnetic field, is limited by atomic properties and scanner physics. Modern sampling techniques termed compressed sensing have nevertheless demonstrated how near perfect reconstructions are possible from undersampled, accelerated acquisitions, showing promise for more efficient MR acquisition paradigms. At the same time, information extraction from MR images through image analysis implies a considerable dimensionality reduction, in which an image is processed for the extraction of a few clinically useful parameters. This signals an inefficient handling of information in the separated treatment of acquisition and analysis that could be tackled by joining these two essential stages of the imaging pipeline. In this thesis, we explore the use of adaptive sparse modelling for novel acquisition strategies of cardiac cine MR data. Conventional compressed sensing MR acquisition relies on fixed basis transforms for sparse modelling, which are only able to guarantee suboptimal sparse modelling. We introduce spatio-temporal dictionaries that are able to optimally adapt sparse modelling by absorbing salient features of cardiac cine data, and demonstrate how they can outperform sampling methods based on fixed basis transforms. Additionally, we extend the framework introduced to handle parallel data acquisition. Given the flexibility of the formulation, we show how it can be combined with a labelling model that provides a segmentation of the image as a by-product of the reconstruction, hence performing joint reconstruction and analysis.Open Acces

Magnetic Resonance Imaging of Short-T2 Tissues with Applications for Quantifying Cortical Bone Water and Myelin

The human body contains a variety of tissue species with short T2 ranging from a few microseconds to hundreds of microseconds. Detection and quantification of these short-T2 species is of considerable clinical and scientific interest. Cortical bone water and myelin are two of the most important tissue constituents. Quantification of cortical bone water concentration allows for indirect estimation of bone pore volume and noninvasive assessment of bone quality. Myelin is essential for the proper functioning of the central nervous system (CNS). Direct assessment of myelin would reveal CNS abnormalities and enhance our understanding of neurological diseases. However, conventional MRI with echo times of several milliseconds or longer is unable to detect these short-lived MR signals. Recent advances in MRI technology and hardware have enabled development of a number of short-T2 imaging techniques, key among which are ultra-short echo time (UTE) imaging, zero echo time (ZTE) imaging, and sweep imaging with Fourier transform (SWIFT). While these pulse sequences are able to detect short-T2 species, they still suffer from signal interference between different T2 tissue constituents, image artifacts and excessive scan time. These are primary technical hurdles for application to whole-body clinical scanners. In this thesis research, new MRI techniques for improving short-T2 tissue imaging have been developed to address these challenges with a focus on direct detection and quantification of cortical bone water and myelin on a clinical MRI scanner. The first focus of this research was to optimize long-T2 suppression in UTE imaging. Saturation and adiabatic RF pulses were designed to achieve maximum long-T2 suppression while maximizing the signal from short-T2 species. The imaging protocols were optimized by Bloch equation simulations and were validated using phantom and in vivo experiments. The results show excellent short-T2 contrast with these optimized pulse sequences. The problem of blurring artifacts resulting from the inhomogeneous excitation profile of the rectangular pulses in ZTE imaging was addressed. The proposed approach involves quadratic phase-modulated RF excitation and iterative solution of an inverse problem formulated from the signal model of ZTE imaging and is shown to effectively remove the image artifacts. Subsequently image acquisition efficiency was improved in order to attain clinically-feasible scan times. To accelerate the acquisition speed in UTE and ZTE imaging, compressed sensing was applied with a hybrid 3D UTE sequence. Further, the pulse sequence and reconstruction procedure were modified to enable anisotropic field-of-view shape conforming to the geometry of the elongated imaged object. These enhanced acquisition techniques were applied to the detection and quantification of cortical bone water. A new biomarker, the suppression ratio (a ratio image derived from two UTE images, one without and the other with long-T2 suppression), was conceived as a surrogate measure of cortical bone porosity. Experimental data suggest the suppression ratio may be a more direct measure of porosity than previously measured total bone water concentration. Lastly, the feasibility of directly detecting and quantifying spatially-resolved myelin concentration with a clinical imager was explored, both theoretically and experimentally. Bloch equation simulations were conducted to investigate the intrinsic image resolution and the fraction of detectable myelin signal under current scanner hardware constraints. The feasibility of quantitative ZTE imaging of myelin extract and lamb spinal cord at 3T was demonstrated. The technological advances achieved in this dissertation research may facilitate translation of short-T2 MRI methods from the laboratory to the clinic

Artefact Reduction Methods for Iterative Reconstruction in Full-fan Cone Beam CT Radiotherapy Applications

A cone beam CT (CBCT) system acquires two-dimensional projection images of an imaging object from multiple angles in one single rotation and reconstructs the object geometry in three dimensions for volumetric visualization. It is mounted on most modern linear accelerators and is routinely used in radiotherapy to verify patient positioning, monitor patient contour changes throughout the course of treatment, and enable adaptive radiotherapy planning. Iterative image reconstruction algorithms use mathematical methods to iteratively solve the reconstruction problem. Iterative algorithms have demonstrated improvement in image quality and / or reduction in imaging dose over traditional filtered back-projection (FBP) methods. However, despite the advancement in computer technology and growing availability of open-source iterative algorithms, clinical implementation of iterative CBCT has been limited. This thesis does not report development of codes for new iterative image reconstruction algorithms. It focuses on bridging the gap between the algorithm and its implementation by addressing artefacts that are the results of imperfections from the raw projections and from the imaging geometry. Such artefacts can severely degrade image quality and cannot be removed by iterative algorithms alone. Practical solutions to solving these artefacts will be presented and this in turn will better enable clinical implementation of iterative CBCT reconstruction