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Diffuse optical tomography for 3D imaging in breast cancer and lymphoedema

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posted on 2022-03-28, 15:34 authored by Ao Chen
Diffuse optimal tomography (DOT) is an emerging non-invasive and inexpensive medical imaging modality which utilises near infrared light in certain spectral ranges to examine the tissues, and reconstructs the distribution of intensity of optical parameters of internal organs through the measurement of optical intensity distribution on the tissue surface. In order to produce high quality imaging, we need to build a mathematical model which can accurately describe the photon transmission in biological tissue. In present research, diffusion equation is commonly used as the forward model in DOT, where the diffusion equation is a diffusion approximation of the radiative transfer equation that states the transmission of photons in the tissue. In order to solve the mathematics efficiently and to finalise the quality DOT images, this report studies the mathematical models and the image reconstruction algorithms. In this project, we have constructed a laboratory DOT prototype which has a 633 nm laser and a photondiode circuit. Moreover, this project presents mathematical expressions of forward problems, which is a photon transmission model in diffusion equation that is based on radiative equation, and solves the inverse problem which is DOT image reconstruction via Gauss-Newton and Levenberg-Marquardt models. The reconstruction results of an Electrical impedance tomography and diffuse optical tomography reconstruction software EIDORS) simulation under a 2 dimensional model with different optical coefficients and the validity of the image reconstruction algorithm are presented.

History

Table of Contents

1. Introduction -- 2. Other related works and scientific research -- 3. Project procedures -- 4. Electrical impedance tomography and diffuse optical tomography reconstruction software (EIDORS) 3D image construction -- 5. Results -- 6. Discussion -= 7. Conclusions -- 8. Abbreviations -- Appendices -- Bibliography.

Notes

Empirical thesis. Bibliography: pages 73-78

Awarding Institution

Macquarie University

Degree Type

Thesis bachelor honours

Degree

BSc (Hons), Macquarie University, Faculty of Science and Engineering, School of Engineering

Department, Centre or School

School of Engineering

Year of Award

2017

Principal Supervisor

Yves De Deenes

Rights

Copyright Ao Chen 2017. Copyright disclaimer: http://mq.edu.au/library/copyright

Language

English

Extent

1 online resource (xv, 79 pages colour illustrations)

Former Identifiers

mq:70431 http://hdl.handle.net/1959.14/1263697

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