Reconstruction algorithms for multispectral diffraction imaging

Thesis (Ph.D.)--Boston UniversityIn conventional Computed Tomography (CT) systems, a single X-ray source spectrum is used to radiate an object and the total transmitted intensity is measured to construct the spatial linear attenuation coefficient (LAC) distribution. Such scalar information is adequate for visualization of interior physical structures, but additional dimensions would be useful to characterize the nature of the structures. By imaging using broadband radiation and collecting energy-sensitive measurement information, one can generate images of additional energy-dependent properties that can be used to characterize the nature of specific areas in the object of interest. In this thesis, we explore novel imaging modalities that use broadband sources and energy-sensitive detection to generate images of energy-dependent properties of a region, with the objective of providing high quality information for material component identification. We explore two classes of imaging problems: 1) excitation using broad spectrum sub-millimeter radiation in the Terahertz regime and measure- ment of the diffracted Terahertz (THz) field to construct the spatial distribution of complex refractive index at multiple frequencies; 2) excitation using broad spectrum X-ray sources and measurement of coherent scatter radiation to image the spatial distribution of coherent-scatter form factors. For these modalities, we extend approaches developed for multimodal imaging and propose new reconstruction algorithms that impose regularization structure such as common object boundaries across reconstructed regions at different frequencies. We also explore reconstruction techniques that incorporate prior knowledge in the form of spectral parametrization, sparse representations over redundant dictionaries and explore the advantage and disadvantages of these techniques in terms of image quality and potential for accurate material characterization. We use the proposed reconstruction techniques to explore alternative architectures with reduced scanning time and increased signal-to-noise ratio, including THz diffraction tomography, limited angle X-ray diffraction tomography and the use of coded aperture masks. Numerical experiments and Monte Carlo simulations were conducted to compare performances of the developed methods, and validate the studied architectures as viable options for imaging of energy-dependent properties

Passive element enriched photoacoustic computed tomography (PER PACT) for simultaneous imaging of acoustic propagation properties and light absorption\ud

We present a ‘hybrid’ imaging approach which can image both light absorption properties and acoustic transmission properties of an object in a two-dimensional slice using a computed tomography (CT) photoacoustic imager. The ultrasound transmission measurement method uses a strong optical absorber of small cross-section placed in the path of the light illuminating the sample. This absorber, which we call a passive element acts as a source of ultrasound. The interaction of ultrasound with the sample can be measured in transmission, using the same ultrasound detector used for photoacoustics. Such measurements are made at various angles around the sample in a CT approach. Images of the ultrasound propagation parameters, attenuation and speed of sound, can be reconstructed by inversion of a measurement model. We validate the method on specially designed phantoms and biological specimens. The obtained images are quantitative in terms of the shape, size, location, and acoustic properties of the examined heterogeneitie

Signal processing based method for solving inverse scattering problems

The problem of reconstructing an image of the permittivity distribution inside a penetrable and strongly scattering object from a finite number of noisy scattered field measurements has always been very challenging because it is ill-posed in nature. Several techniques have been developed which are either computationally very expensive or typically require the object to be weakly scattering. I have developed here a non-linear signal processing method, which will recover images for both strong scatterers and weak scatterers. This nonlinear or cepstral filtering method requires that the scattered field data is first preprocessed to generate a minimum phase function in the object domain. In 2-D or higher dimensional problems, I describe the conditions for minimum phase and demonstrate how an artificial reference wave can be numerically combined with measured complex scattering data in order to enforce this condition, by satisfying Rouche‘s theorem. In the cepstral domain one can filter the frequencies associated with an object from those of the scattered field. After filtering, the next step is to inverse Fourier transform these data and exponentiate to recover the image of the object under test. In addition I also investigate the scattered field sampling requirements for the inverse scattering problem. The proposed inversion technique is applied to the measured experimental data to recover both shape and relative permittivity of unknown objects. The obtained results confirm the effectiveness of this algorithm and show that one can identify optimal parameters for the reference wave and an optimal procedure that results in good reconstructions of a penetrable, strongly scattering permittivity distribution

Model-based Tomographic Reconstruction Literature Search

In the process of preparing a proposal for internal research funding, a literature search was conducted on the subject of model-based tomographic reconstruction (MBTR). The purpose of the search was to ensure that the proposed research would not replicate any previous work. We found that the overwhelming majority of work on MBTR which used parameterized models of the object was theoretical in nature. Only three researchers had applied the technique to actual data. In this note, we summarize the findings of the literature search

Reflection Mode Diffraction Tomography

In the field of ultrasound diffraction tomography, a cross section of a weakly scattering object is reconstructed from measurements of the sound scattered from the insonified object. This research studies tomographic imaging algorithms that deal only with the sound that is backscattered from the object. The use of the backscattered sound provides higher resolution reconstructions due to the higher spatial frequency information about the object that is obtained from the backscatter. Unfortunately the cost of the high frequency information contained in the backscatter is the loss of low frequency information. Different approaches to compensate for this loss are discussed. An additional benefit of reflection mode tomography is that it has the advantage of requiring only 180° access to the object whereas transmission mode requires 360°. The charter of this research is to explore the effectiveness of current reflection mode diffraction tomography algorithms and to theoretically develop, as well as experimentally verify, new algorithms. Different scanning geometries with different methods of insonification are explored. Many different approaches to the analysis of the problem are taken

Application and Challenges of Signal Processing Techniques for Lamb Waves Structural Integrity Evaluation: Part B-Defects Imaging and Recognition Techniques

The wavefield of Lamb waves is yielded by the feature of plate-like structures. And many defects imaging techniques and intelligent recognition algorithms have been developed for defects location, sizing and recognition through analyzing the parameters of received Lamb waves signals including the arrival time, attenuation, amplitude and phase, etc. In this chapter, we give a briefly review about the defects imaging techniques and the intelligent recognition algorithms. Considering the available parameters of Lamb waves signals and the setting of detection/monitoring systems, we roughly divide the defect location and sizing techniques into four categories, including the sparse array imaging techniques, the tomography techniques, the compact array techniques, and full wavefield imaging techniques. The principle of them is introduced. Meanwhile, the intelligent recognition techniques based on various of intelligent recognition algorithms that have been widely used to analyze Lamb waves signals in the research of defect recognition are reviewed, including the support vector machine, Bayesian methodology, and the neural networks

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