Sub-band denoising and spline curve fitting techniques for hemodynamic measurements
| Autor: | Yuan-Yu Hsu, Kang-Ping Lin, Hong-Dun Lin, Hsiao-Ling Huang, Ing-Yi Chen, Chi-Hsien Chen |
|---|---|
| Rok vydání: | 2003 |
| Předmět: |
medicine.diagnostic_test
Hemodynamic measurements Computer science business.industry Image quality Noise reduction Hemodynamics Magnetic resonance imaging Image processing White matter medicine.anatomical_structure medicine Computer vision Artificial intelligence business Perfusion Smoothing Biomedical engineering |
| Zdroj: | IFAC Proceedings Volumes. 36:259-263 |
| ISSN: | 1474-6670 |
| DOI: | 10.1016/s1474-6670(17)33512-7 |
| Popis: | Non-invasive perfusion MRI is useful for investigating brain functions via various hernodynarnic measurements includes CBV, CBF, and MTT. The measurement accuracy is affected by poor signal-to-noise ratio image quality. In this study, a sub-band denoising and spline curve fitting processes are proposed to improve image quality for better hemodynamic quantitative analysis results. Ten sets of perfusion MRI data and corresponding PET images were used to validate the performance. As a result, the semi-quantitative analysis result of mean gray to white matter CBF ratio is 2.10±0.34. The evaluated ratio of brain tissues in perfusion MRI is comparable to PET technique in less than 1-% difference in average. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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