Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Multi-disciplinary Studies | en_US |
| dc.contributor | Department of Electronic and Information Engineering | en_US |
| dc.creator | Wong, Wai-ting | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/4649 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Software system for medical image reconstruction and dynamic system modeling studies | en_US |
| dcterms.abstract | Modern functional imaging with its unique capability of extracting quantitative information from complex dynamic processes has opened a new window for scientific and biomedical research. For instance, the parametric images of glucose metabolism for the human brain derived from dynamic study with Positron Emission Tomography (PET) provide quantitative information for regional or local glucose metabolic process in the human brain, which is previously not available. Such images play an important role to assess human brain function. However, it is not an easy job to derive accurate functional images based on biomedical process modeling and parameter estimation, due to the complicated situations in data acquisition, image reconstruction with noisy data, system modeling and parameter estimation. Great attention has been paid to the research on these topics for the last few decades, and numerous significant results have been reported in these areas. It would be ideal if there is a dedicated system which can integrate these related results to simulate the whole process of the generation of physiological function images from the noisy raw data acquired from the medical imaging modalities such as PET and single photon emission computed tomography (SPECT). In this thesis, the main objective of this work is to develop a powerful and useful software package that integrated techniques for image reconstruction and dynamic system modeling which is a worthy facility of medical (clinical) and non-medical (teaching and research) applications. In these cases, some innovative features such as noise corruption on the projection data and a number of statistical tests for parameter estimation are included in order to simulate real conditions and to help interpretation on the results of parameter estimation. Moreover, one of the most important innovative features of this project is the combination of back-projection and modeling which is not yet available. In addition to the scientific contribution to the field of functional imaging, this project provides direct benefits to researchers, engineers, medical doctors, and students to conduct various simulations for the process of the generation of quantitative functional images, to study the performance of various newly developed signal processing algorithms and to develop new techniques to improve the quality for image reconstruction and dynamic system modeling. | en_US |
| dcterms.extent | xiv, 129 leaves : ill. ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2000 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Imaging systems in medicine | en_US |
| dcterms.LCSH | Diagnostic imaging -- Data processing | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b15321034.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.88 MB | Adobe PDF | View/Open |
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