Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp018049g766q
 Title: Image Enhancement in Optics and Ultrasound using Nonlinearity Authors: Lu, Jen-Tang Advisors: Fleischer, Jason W. Contributors: Electrical Engineering Department Keywords: Computational ImagingImaging ProcessingMedical UltrasoundNonlinear OpticsOptical ImagingPhase Retreival Subjects: OpticsMedical imaging Issue Date: 2017 Publisher: Princeton, NJ : Princeton University Abstract: Conventional imaging systems based on linear wave propagation suffer many limitations, including diffraction-limited resolution, a trade-of between contrast and resolution, and limited sensitivity to phase. In this dissertation, we overcome these limits by developing new imaging schemes using nonlinear effects and computational imaging techniques. The methods are demonstrated in optical imaging and medical ultrasound imaging. The first part of the thesis focuses on enhancing phase reconstruction using nonlinear propagation. The feedback between amplitude and phase upon nonlinear propagation makes the system very sensitive to phase, which we demonstrate experimentally with a photorefractive crystal. Phase matching (conservation of energy and momentum) leads to a zero-crossing convergence profile, where the known amplitude error and the unknown phase error reach their minimum at the same iteration. This zero crossing, not present in linear systems, provides a previously unavailable criterion for stopping the iterative algorithm. The nonlinear algorithm performs twice as well as conventional algorithms using linear propagation. In the second part of the dissertation, we use an electro-optic spatial light modulator to produce nonlinear effects without a physical medium. Specifically, we use feedback between the diffraction pattern of an object and the illumination pattern on the modulator. This "digital" nonlinearity greatly facilitates nonlinear optics, because it works for any light intensity, has a fast response time, operates over a broad bandwidth, is dynamically adjustable, and is compatible with nearly any arbitrarily mathematical form. We demonstrate the method in phase imaging using both coherent and incoherent light. In the final part of the thesis, we apply these ideas to ultrasound imaging. We consider both traditional nonlinear imaging (tissue harmonic imaging) and tissue-specific imaging (object-dependent adjustments to the speed of sound). We then numerically compare these images with the fundamental image. By leveraging the mutual information between the signals, we create a composite image with better contrast, higher resolution, lower noise, fewer artifacts, and more tissue-specific response than is possible with each image individually. URI: http://arks.princeton.edu/ark:/88435/dsp018049g766q Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: catalog.princeton.edu Type of Material: Academic dissertations (Ph.D.) Language: en Appears in Collections: Electrical Engineering

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