Tissue imaging using nonlinear laser scanning microscope

The importance for a fast and efficient imaging technique is essential today for imaging of biological tissues. From retinal diseases and disorders such as Retinal Vein Occlusion, Diabetic Retinopathy, and Retinal Tear or Detachments to cancer research in the liver, there are sophisticated technolog...

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Main Author: Tay, Kenneth ZiHan
Other Authors: Liu Quan
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/75631
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-756312023-03-03T15:35:14Z Tissue imaging using nonlinear laser scanning microscope Tay, Kenneth ZiHan Liu Quan School of Chemical and Biomedical Engineering DRNTU::Science::Physics::Optics and light The importance for a fast and efficient imaging technique is essential today for imaging of biological tissues. From retinal diseases and disorders such as Retinal Vein Occlusion, Diabetic Retinopathy, and Retinal Tear or Detachments to cancer research in the liver, there are sophisticated technologies available today to diagnose these diseases on a macroscopic level, but the optimum parameters aren’t pre-determined prior to the imaging of these biological tissues. A novel technology called two-photon microscopy, which is based on the principle of Confocal Laser Scanning Microscopy and Two-Photon Excitation is being explored for its application in imaging the microstructures of the retina in vivo. This project thus aims to determine the optimal parameters in the imaging of biological tissues using the principles of Confocal Laser Scanning Microscopy to carry out ex-vivo Two-Photon Microscopy. Ultimately obtaining successful images to observe and understand the microstructures of biological tissues such as the retina. Bachelor of Engineering (Chemical and Biomolecular Engineering) 2018-06-05T09:20:01Z 2018-06-05T09:20:01Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75631 en Nanyang Technological University 51 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Physics::Optics and light
spellingShingle DRNTU::Science::Physics::Optics and light
Tay, Kenneth ZiHan
Tissue imaging using nonlinear laser scanning microscope
description The importance for a fast and efficient imaging technique is essential today for imaging of biological tissues. From retinal diseases and disorders such as Retinal Vein Occlusion, Diabetic Retinopathy, and Retinal Tear or Detachments to cancer research in the liver, there are sophisticated technologies available today to diagnose these diseases on a macroscopic level, but the optimum parameters aren’t pre-determined prior to the imaging of these biological tissues. A novel technology called two-photon microscopy, which is based on the principle of Confocal Laser Scanning Microscopy and Two-Photon Excitation is being explored for its application in imaging the microstructures of the retina in vivo. This project thus aims to determine the optimal parameters in the imaging of biological tissues using the principles of Confocal Laser Scanning Microscopy to carry out ex-vivo Two-Photon Microscopy. Ultimately obtaining successful images to observe and understand the microstructures of biological tissues such as the retina.
author2 Liu Quan
author_facet Liu Quan
Tay, Kenneth ZiHan
format Final Year Project
author Tay, Kenneth ZiHan
author_sort Tay, Kenneth ZiHan
title Tissue imaging using nonlinear laser scanning microscope
title_short Tissue imaging using nonlinear laser scanning microscope
title_full Tissue imaging using nonlinear laser scanning microscope
title_fullStr Tissue imaging using nonlinear laser scanning microscope
title_full_unstemmed Tissue imaging using nonlinear laser scanning microscope
title_sort tissue imaging using nonlinear laser scanning microscope
publishDate 2018
url http://hdl.handle.net/10356/75631
_version_ 1759854913712553984