Computational microscopy for sample analysis
Name
893615226-MIT.pdf
Description
Full printable version
Size
4.55 MB
Format
Adobe PDF
Checksum (MD5)
cada8e82d3e765c8ed886fbd8e8ad7a3
Author(s)
Ikoma, Hayato
Advisor(s)
Ramesh Raskar.
Date Issued
2014
Publisher
Massachusetts Institute of Technology
Abstract
Computational microscopy is an emerging technology which extends the capabilities of optical microscopy with the help of computation. One of the notable example is super resolution fluorescence microscopy which achieves sub-wavelength resolution. This thesis explores the novel application of computational imaging methods to fluorescence microscopy and oblique illumination microscopy. In fluorescence spectroscopy, we have developed a novel nonlinear matrix unmixing algorithm to separate fluorescence spectra distorted by absorption effect. By extending the method to tensor form, we have also demonstrated the performance of a nonlinear fluorescence tensor unmixing algorithm on spectral fluorescence imaging. In the future, this algorithm may be applied to fluorescence unmixing in deep tissue imaging. The performance of the two algorithms were examined on simulation and experiments. In another project, we applied switchable multiple oblique illuminations to reflected-light microscopy. While the proposed system is easily implemented compared to existing methods, we demonstrate that the microscope detects the direction of surface roughness whose height is as small as illumination wavelength.
Description
Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2014.
46
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 41-44).
Subjects
Architecture. Program in Media Arts and Sciences.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
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