Version 1
: Received: 9 January 2023 / Approved: 16 January 2023 / Online: 16 January 2023 (09:43:02 CET)
How to cite:
Peirson, C. Theory, Advantages, Applications and Future of Diffuse Optical Tomography. Preprints2023, 2023010281. https://doi.org/10.20944/preprints202301.0281.v1
Peirson, C. Theory, Advantages, Applications and Future of Diffuse Optical Tomography. Preprints 2023, 2023010281. https://doi.org/10.20944/preprints202301.0281.v1
Peirson, C. Theory, Advantages, Applications and Future of Diffuse Optical Tomography. Preprints2023, 2023010281. https://doi.org/10.20944/preprints202301.0281.v1
APA Style
Peirson, C. (2023). Theory, Advantages, Applications and Future of Diffuse Optical Tomography. Preprints. https://doi.org/10.20944/preprints202301.0281.v1
Chicago/Turabian Style
Peirson, C. 2023 "Theory, Advantages, Applications and Future of Diffuse Optical Tomography" Preprints. https://doi.org/10.20944/preprints202301.0281.v1
Abstract
Diffuse optical tomography (DOT) is a medical imaging procedure using light to measure the geometric and working properties of cells, for instance, oxygen consumption, water content, and fat percentage in the tissue by performing three-dimensional visualization of the tissue. This paper aims to explain the theory behind diffuse optical tomography imaging and how the technology works. The paper explains how photon migration techniques based on diffusion theory can be used to image the optical properties of tissue. There are several reasons why near-infrared (NIR) imaging is the most effective method in terms of recovering optical parameters quantitatively in the near-infrared region. The author discusses the methods in detail. This research also presents various advantages, practical uses, and potential problems that have been related to DOT in this work. There is also a brief discussion of current research developments in medical imaging using near-infrared wavelengths, and what the future holds for that area.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
