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ABSTRACT: Localizing interictal epileptic activities is a difficult problem in clinical practice. We report a novel noninvasive technique, resting functional magnetic resonance imaging (fMRI) with spatio-temporal independent component analysis (ICA), for localizing interictal epileptic activities. First, the fMRI data is separated into independent spatial patterns by spatial-ICA, and the patterns with Z-values larger than a threshold are selected as the potential spatial patterns of the epileptic activities. Second, the temporal series of the active points in the selected patterns are separated by temporal-ICA, and the component with the biggest Gaussian deviation (kurtosis) is selected as the representative of the epileptic discharge activity in a sub-region. Finally, those spatial sub-regions, which have distinct epileptic discharge activities confirmed by temporal-ICA are considered as the epileptic foci. This method was applied to fMRI data of six epileptic patients, and the results are consistent with the clinical assessment. Though more studies are required to validate this technique, the above preliminary results demonstrate the potential of using the resting fMRI with spatio-temporal ICA to detect and localize latent epileptic activities.
Brain Topography 02/2006; 19(1-2):21-8. · 3.45 Impact Factor
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Advances in Natural Computation, Second International Conference, ICNC 2006, Xi'an, China, September 24-28, 2006. Proceedings, Part II; 01/2006
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ABSTRACT: a large scale of remote sensing data is obtained every day with the rapid development of remote sensing technology. To store these data will need a large space and to process and analyze these data will need high computational capabilities. Remote sensing data usually are managed by relational database. But with rapid development of the technologies, the data increased in geometric series. Traditional database cannot store and manage these data effectively. Every department will usually build its own database independently. The databases are islands apart from others. The users who want to use the data have to search every database to find the required and copy them to user's own database. That is time consuming and annoying. Grid is the new technology that provides new ways to solve these problems. Grid integrates the resources and computational capabilities in the Internet or intranet. It provides service-oriented architecture. Bases on grid technology, the new remote sensing database will achieve automatic storage and management. The databases in grid pool combines and acted as one database. It is expressed by services. Users get the results by various services and needn't copy them to the local database if they require.
Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. Proceedings. 2005 IEEE International; 08/2005
