Model-based high-density functional diffuse optical tomography of human brain

Zhan, Yuxuan (2013). Model-based high-density functional diffuse optical tomography of human brain. University of Birmingham. Ph.D.

[img]
Preview
Zhan13PhD.pdf
PDF - Redacted Version

Download (7MB)

Abstract

Functional diffuse optical tomography (fDOT) is an emerging functional neuroimaging technology that allows non-invasive imaging of human brain functions. The aims of this thesis are to enhance current understandings and knowledge of fDOT image quality and to improve on its imaging performance using a model-based approach. Specifically we have established a computationally efficient finite element method (FEM)-based routine to conduct MRI-guided fDOT simulation studies. Based on this framework, we have demonstrated that HD-fDOT is capable of imaging focal haemodynamic response up to 18 mm depth below the human scalp surface at 10 mm image resolution and localisation accuracy, allowing distinguishability of gyri. In addition, we also investigated the effects of uncertainty in the background tissue optical property on HD-fDOT image quality. Our multi-model comparative study has concluded that the use of a proposed homogeneous background absorption fitting scheme in HD-fDOT can minimise the chances of obtaining sub-optimal image quality due to uncertainty in background tissue optical properties. Finally we have addressed and resolved a regularisation problem in spectral fDOT that was previously not understood. Our proposed singular-decomposition-based regularisation method has been shown to reduce imaging crosstalk observed in both spectral and non-spectral fDOT.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
Supervisor(s):
Supervisor(s)EmailORCID
Dehghani, HamidUNSPECIFIEDUNSPECIFIED
Licence:
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Computer Science
Funders: None/not applicable
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
URI: http://etheses.bham.ac.uk/id/eprint/4450

Actions

Request a Correction Request a Correction
View Item View Item

Downloads

Downloads per month over past year