A framework on automated ventricular analysis of CMR images
| Autor: | A. V. Nageswararao, S. Srinivasan |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Cardiac function curve
Short axis medicine.diagnostic_test Computer science Functional features Feature extraction Magnetic resonance imaging Image segmentation Level set cardiovascular system medicine Segmentation cardiovascular diseases circulatory and respiratory physiology Biomedical engineering |
| Zdroj: | 2017 Trends in Industrial Measurement and Automation (TIMA). |
| DOI: | 10.1109/tima.2017.8064800 |
| Popis: | Magnetic resonance imaging is a highly advanced reference imaging modality for cardiac morphology, function and perfusion in humans. A framework is proposed for automatic ventricular analysis using cardiac magnetic resonance images. The short axis cine CMR images are corrected for intensity-inhomogeneity using Bias Corrected Fuzzy C-Means method. Ventricular Segmentation of CMR images is important to quantitatively analyze global and regional cardiac function. Extraction of morphological and functional features of CMR images helps in diagnosis of various cardiovascular diseases. The effectiveness of the proposed framework is verified by the experimental results on real CMR images. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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