Assessment of cardiac mass from tagged magnetic resonance images
| Autor: | El-Sayed H. Ibrahim, Ayman M. Khalifa, Ahmed S. Fahmy, Hossam El-Rewaidy, Abram W. Makram |
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| Rok vydání: | 2015 |
| Předmět: |
Heart Diseases
Computer science Contrast Media Magnetic Resonance Imaging Cine Signal Two stages 030218 nuclear medicine & medical imaging Scan time 03 medical and health sciences 0302 clinical medicine Image Interpretation Computer-Assisted medicine Humans Radiology Nuclear Medicine and imaging Principal Component Analysis medicine.diagnostic_test business.industry Magnetic resonance imaging Pattern recognition Magnetic Resonance Imaging Cardiac mass Global function Ventricular volume Artificial intelligence Ventricular mass business Nuclear medicine Algorithms |
| Zdroj: | Japanese Journal of Radiology. 34:158-165 |
| ISSN: | 1867-108X 1867-1071 |
| DOI: | 10.1007/s11604-015-0504-4 |
| Popis: | Tagged and cine magnetic resonance imaging (tMRI and cMRI) techniques are used for evaluating regional and global heart function, respectively. Measuring global function parameters directly from tMRI is challenging due to the obstruction of the anatomical structure by the tagging pattern. The purpose of this study was to develop a method for processing the tMRI images to improve the myocardium-blood contrast in order to estimate global function parameters from the processed images. The developed method consists of two stages: (1) removing the tagging pattern based on analyzing and modeling the signal distribution in the image’s k-space, and (2) enhancing the blood-myocardium contrast based on analyzing the signal intensity variability in the two tissues. The developed method is implemented on images from twelve human subjects. Ventricular mass measured with the developed method showed good agreement with that measured from gold-standard cMRI images. Further, preliminary results on measuring ventricular volume using the developed method are presented. The promising results in this study show the potential of the developed method for evaluating both regional and global heart function from a single set of tMRI images, with associated reduction in scan time and patient discomfort. |
| Databáze: | OpenAIRE |
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