Analysis of cardiac velocity MR images using fuzzy clustering
| Autor: | Ahmed Ismail Shihab, Peter Burger |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
Fuzzy clustering
medicine.diagnostic_test Plane (geometry) Computer science business.industry Quantitative Biology::Tissues and Organs Physics::Medical Physics Relaxation (iterative method) Magnetic resonance imaging Fuzzy logic Computer Science::Computer Vision and Pattern Recognition Modulation (music) medicine Computer vision Artificial intelligence Mr images Cluster analysis business Cartography |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.312561 |
| Popis: | Velocity Magnetic Resonance (MR) images are a novel form of medical images. A special gradient-modulation technique is utilized to capture motion velocity of tissue and blood. As well as the tissue density image, there are also other images that depict the velocity components along axes defined relative to the plane of imaging. The images are of the cardiac region and are aligned with the short-axis of the left ventricle. We present the results of clustering cardiac image sequences using the Fuzzy c-Means (FCM) algorithm. Our paper demonstrates how the application of clustering to one frame in the cine sequence of images can be utilized in order to track reasonably well the contraction and relaxation of the Left Ventricle. Our paper shows that this imaging technique is generally accurate and certainly adds to the information already contained in the tissue density images. |
| Databáze: | OpenAIRE |
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