Ultrahigh-resolution, deep-penetration spectral-domain optical coherence tomography
Name
1083780302-MIT.pdf
Description
Full printable version
Size
13.02 MB
Format
Adobe PDF
Checksum (MD5)
73412b044ea25959f526e9e11a6f2cb5
Author(s)
Bernstein, Liane (Liane Sarah Bel)
Advisor(s)
Seok-Hyun (Andy) Yun and Roger G. Mark.
Alternative Title
Ultrahigh-resolution, deep-penetration spectral-domain OCT
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
Optical coherence tomography (OCT) is a label-free optical imaging modality that allows non-invasive in-depth visualization of microscopic structures in samples. With a typical resolution of 10-15 [mu]m and a penetration of up to a few mm, OCT is widely used for medical diagnoses in fields such as ophthalmology and cardiology. However, the more common diagnostic tool in the microscopic regime of medical imaging is histology, an invasive technique requiring tissue biopsy. Its resolution can be as small as 0.2 [mu]m, allowing the visualization of subcellular structures. To help bridge this gap between OCT and histology, ultrahigh-resolution OCT systems have been developed, with resolutions on the order of 1 [mu]m. Yet their application remains limited, since they employ shorter-wavelength sources, reducing penetration in tissue. We have designed and built a spectral-domain ultrahigh-resolution, deep-penetration OCT system centered at 1290 nm with axial and lateral resolutions of 2 and 5 [mu]m, respectively. To our knowledge, this is the best axial resolution obtained for a highspeed OCT system centered this deeply in the infrared. We demonstrate imaging of the cardiac conduction system, which could eventually be used for intraoperative identification of conducting tissue. In addition, we show images of the corneo-scleral angle, which could help properly diagnose primary angle-closure glaucoma. Other potential applications are also discussed.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 73-77).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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