Dissertation Defense Announcement
Herff College of Engineering announces the Final Dissertation Defense of
for the Degree of Doctor of Philosophy
February 12, 2019 at 1:00 PM in Engineering Science Building, Room 222
Advisor: Dr. Chrysanthe Preza
Three-dimensional (3D) image reconstruction for structured illumination microscopy using a 3D tunable pattern
ABSTRACT: Specific needs in live-cell microscopy necessitate moving fluorescence microscopy toward 3D imaging with enhanced spatial and temporal resolution. Exciting the sample by non-uniform illumination instead of uniform illumination is the main idea of developing techniques to address Abbe's diffraction limit in the conventional widefield fluorescence microscopy. In this dissertation, we characterized a novel tunable structured illumination microscopy (SIM) system using a Fresnel biprism illuminated by multiple linear incoherent sources (slits), in which the lateral and axial modulation frequencies of the 3D structured illumination (SI) pattern can be tuned separately. This is a unique feature, which is not the case of conventional SIM systems. First, in order to take advantage of the tunable-frequency 2D-SIM system (using a single slit), we present a computational approach to reconstruct optical-sectioned (OS) images with super-resolution (SR) enhancement (OS-SR double shot approach) by combining data from two lateral modulation frequencies. Moreover, a computational approach to reduce residual fringes evident in the restored images from the Fresnel biprism-based incoherent tunable SIM system is proposed. Second, the 3D SI pattern and the forward imaging model for the tunable-frequency 3D-SIM system (using multiple slits) are verified experimentally and two reconstruction methods have been used to evaluate the achieved OS and SR capabilities. Third, we presented the design of the 3D SI system used in a tunable 3D-SIM setup and discussed its performance in terms of synthetic optical transfer function (OTF). By designing the slit element, we can engineer the frequency response of our 3D-SIM system to always operate at the highest OS and SR performance for a given imaging application. This is the first 3D-SIM setup that enables independent control of the achieved OS and SR capabilities. Finally, we proposed and implemented a new 3D iterative deconvolution approach based on a model that takes into account the axial scanning of the specimen during the data acquisition as in commercial microscopes. The method minimizes the mean squared error using the conjugate gradient descent optimization method. To our knowledge, such a restoration method has not been published to date.