Automatic Magnetic Resonance Tissue Characterization for Three-Dimensional Magnetic Resonance Imaging of the Brain
| Autor: | W E Phillips nd, M L Silbiger, S Phuphanich, R.P. Velthuizen |
|---|---|
| Rok vydání: | 1995 |
| Předmět: |
Adult
Male Physics of magnetic resonance imaging Fuzzy clustering Brain Edema Image processing Pattern Recognition Automated Fuzzy Logic Magnetic resonance imaging of the brain Image Processing Computer-Assisted medicine Humans Radiology Nuclear Medicine and imaging Segmentation medicine.diagnostic_test Brain Neoplasms business.industry Magnetic resonance microscopy Magnetic resonance spectroscopic imaging Neoplasms Second Primary Magnetic resonance imaging Pattern recognition Image Enhancement Magnetic Resonance Imaging Data Display Neurology (clinical) Artificial intelligence Neoplasm Recurrence Local Glioblastoma business Algorithms |
| Zdroj: | Journal of Neuroimaging. 5:171-177 |
| ISSN: | 1051-2284 |
| DOI: | 10.1111/jon199553171 |
| Popis: | Computer-assisted diagnostic systems enhance the information available from magnetic resonance imaging. Segmentations are the basis on which three-dimensional volume renderings are made. The application of a raw data-based, operator-independent (automatic), magnetic resonance segmentation technique for tissue differentiation is demonstrated. Segmentation images of vasogenic edema with gross and histopathological correlation are presented for demonstration of the technique. A pixel was classified into a tissue class based on a feature vector using unsupervised fuzzy clustering techniques as the pattern recognition method. Correlation of fuzzy segmentations and gross and histopathology were successfully performed. Based on the results of neuropathological correlation, the application of fuzzy magnetic resonance image segmentation to a patient with a brain tumor and extensive edema represents a viable technique for automatically displaying clinically important tissue differentiation. With this pattern recognition technique, it is possible to generate automatic segmentation images that display diagnostically relevant neuroanatomical and neuropathological tissue contrast information from raw magnetic resonance data for use in three-dimensional volume reconstructions. |
| Databáze: | OpenAIRE |
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