Existing microstructure parameters of computed tomography (CT) are able to compute
architectural properties of the bone from ex-situ and ex-vivo scans while they
are highly affected by the issues of noise and low resolution when applied to clinical
in-vivo imaging. A set of improvements of the standard workflow for the quantitative
computation of micro-structure from clinical in-vivo scans is proposed in this
thesis. Robust methods are proposed (1) for the calibration of density values, (2)
the binarization into bone and marrow phase, (3) fuzzy skeletonization and (4) the
calibration of the CT volumes in particular for the computation of micro-structural
parameters. Furthermore, novel algorithms for the computation of rod-volume fraction
with 3D rose diagrams and fractal approaches are proposed and the application
of local texture operators to diffusion tensor imaging is proposed. Finally an existing
computer program for the application in radiology departments, Structural Insight,
was improved and largely extended.
In particular the methods of the microstructural calibration, the fractal and the
texture operators showed significant improvements of accuracy and precision for
the prediction of fracture risk and the quantitative assessment of the progress of
Alzheimer's disease, in comparison to existing state-of-the art methods. The methods
were tested on artificial and in-vitro data and as well on real-world computed
tomography and magnetic resonance imaging (MRI) studies. The proposed novel
methods improve the computation of bone characteristics from in-vivo CT and MRI
in particular if the methods are combined with each other. In consequence, this
allows to assess more information from existing data or to conduct studies with
less ray exposure and regarding the MRI method in shorter time than nowadays
required.
| Identifer | oai:union.ndltd.org:uns.edu.ar/oai:repositorio.bc.uns.edu.ar:123456789/3414 |
| Date | 07 March 2017 |
| Creators | Thomsen, Felix Sebastian Leo |
| Contributors | Delrieux, Claudio Augusto |
| Publisher | Universidad Nacional del Sur |
| Source Sets | Universidad Nacional del Sur |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation, Text |
| Rights | 2 |
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