Spectral Light Interference Microscopy (SLIM) Using Twisted Nematic Liquid Crystals: Hardware and Software Implemetations
Marar, Abhijit
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/47608
Description
Title
Spectral Light Interference Microscopy (SLIM) Using Twisted Nematic Liquid Crystals: Hardware and Software Implemetations
Author(s)
Marar, Abhijit
Contributor(s)
Popescu, Gabriel
Issue Date
2013-05
Keyword(s)
microscopy
quantitative phase imaging
spectral light interference microscopy
SLIM
Abstract
In light microscopy experiments the information concerning the phase is lost upon recording intensity images. The phase information often contains valuable information on the studied specimen. Spatial Light Interference Microscopy (SLIM) is a powerful imaging method that captures the phase fluctuation across the specimen. This information contains useful information of the imaging target (e.g. morphological thickness, refractive index, dry mass etc.). This thesis focuses on improving the efficiency and compactness of the conventional reflective SLIM setup by building a unified hardware and software solution. On the hardware side, we proposed to use the transmission-based equipment called a spatial light modulator (SLM) based on a twisted nematic crystal display to reduce the overall size and made other necessary changes. On the software side, we integrated different software modules in a common framework to increase consistency and stability. We demonstrate that our system is fully automatic from image acquisition, phase calculation and visualization.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.