Brouwer, H.P. (1995) Fuzzy merging techniques for creating 3D models of the spine. Master's Thesis / Essay, Computing Science.
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Abstract
Scoliosis patients are children in the age of seven to sixteen, who suffer from a curvature of the spine, along with a torsion component (a rotation to the left or the right). In order to be able to treat these patients a 'brace' has to be constructed, this is a corset that forces the body to attain a better posture. Currently this brace is being constructed using a series of (two dimensional) X—ray images of the spine and a plaster cast of the back of the patients. This method is however still far from perfect, and can be improved on many fronts using, amongst others, fuzzy techniques. The first part of this paper describes the search for new imaging techniques that can possibly be used for improving the method. The mean selection criteria have been: the patient must endure minimal stress and minimal risc, the imaging time must be fast and the resulting image of the spine must be accurate. There appeared to be no technique that could meet all the demands, accuracy of the techniques being the main stumbling block. Therefore an attempt was made to try and find a solution by combining data from several promising imaging techniques, namely: ultrasonografy, rastering stereografy and possible in a later stage thermografy and optic tomografy in order to accomplish the required accuracy. In order to construct a syntactic model of the spine, I used data from X—ray images of the spine and foreknowledge on the shape of vertebrae and the spine. Doing this I defined a fuzzy model for 'approximate vertebrae', which models the vertebrae as 'approximate rectangles', and using the structural relations between the vertebrae, I constructed the fuzzy model for 'approximate spines'. This model is shaped like a fuzzy binary tree and can be parsed by fuzzy root—to—frontier tree automata. Both these concepts are explained thoroughly in the paper. Because this model is tailor made for interpreting data that represents different views of the spine emerging from the X—ray images, merging different models in order to construct new fuzzy binary tree models has become very simple and elegant. As an example of this ease of combining, I combined two different models representing two different (two dimensional) views of the spine to a new model representing a three dimensional view of the spine, along with the new corresponding three dimensional 'approximate vertebrae' ('approximate cubes') and 'approximate spines'. Results are visualised using a viewer that can interpret three dimensional structures.
| Item Type: | Thesis (Master's Thesis / Essay) |
|---|---|
| Degree programme: | Computing Science |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 15 Feb 2018 07:29 |
| Last Modified: | 15 Feb 2018 07:29 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/8778 |
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