Signal processing and image reconstruction for scanning tomographic acoustic microscopy
Chiao, Richard Y.
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Permalink
https://hdl.handle.net/2142/20965
Description
Title
Signal processing and image reconstruction for scanning tomographic acoustic microscopy
Author(s)
Chiao, Richard Y.
Issue Date
1990
Doctoral Committee Chair(s)
Lee, Hua
Department of Study
Electrical and Computer Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Language
eng
Abstract
With the advent of high-speed and specialized computers, computed imaging has gained prominence. This thesis is on the application of signal and image processing techniques to address the problems of resolution and noise in the Scanning Laser Acoustic Microscope (SLAM). The SLAM was developed for high-resolution, real-time imaging in biomedical tissue analysis and nondestructive testing. Because of diffraction and the overlapping of depth planes, the SLAM is limited in its ability to image specimens with significant complexity in the depth direction. The Scanning Tomographic Acoustic Microscope (STAM) was proposed to overcome the limitations of the SLAM through the use of holography and tomography. The main objective of the present research is to implement the STAM to demonstrate feasibility and reconstruction improvement.
Implementation of the STAM is complicated by two categories of problems: phase errors in the detected wavefield and misalignment of the tomographic projections. Phase errors are a significant source of degradation in the tomographic reconstruction. Two types of phase errors are identified and modeled, and algorithms are derived for their correction. For multiple-angle tomography, projection registration and alignment are also important. The problems of pose estimation and nonuniform sampling of the tomographic projections are addressed. The general approach to solving these implementation problems is one of modeling and estimation, where the desired quantity is modeled in the projections, and a procedure is derived to estimate the quantity reliably from the known data. Experimental data are used to verify the results.
By addressing the implementation problems, tomographic reconstructions have been obtained which demonstrate feasibility of the STAM and improvement over the SLAM. The reconstruction improvement is interpreted in terms of resolution enhancement and noise suppression. Finally, a quantitative imaging technique which images the propagation velocity is developed for the STAM. Velocity imaging is equivalent to imaging the phase of the detected wavefield, which yields the velocity information given the data acquisition geometry. Besides providing a method for quantitative imaging, this algorithm also allows the phase to be used for image interpretation. Experimental results using both synthetic and biological specimens are used to demonstrate the algorithms.
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