Follow-up studies of human organs with certain abnormalities are necessary to monitor the effect of therapy and the extent of recovery. But, current approaches are limited to subjective estimation by physicians. In this paper, we present a comparative visualization and objective analysis system for long-term follow-up studies using cardiac MR images. This system uses dynamic cardiac models in order to effectively analyze huge cardiac datasets acquired at different times and applies the data hierarchy that is proper for effectively managing the multi-dimensional cardiac images, dynamic models and analyzed parameters for each patient. The proposed system provides various quantitative analysis functions for global and local diagnostic parameters of ventricles based on the physical properties of the heart. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Kim, M. J., Choi, S. M., Choi, Y. J., & Kim, M. H. (2006). Multi-dimensional visualization and analysis of cardiac MR images during long-term follow-up. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4142 LNCS, pp. 602–611). Springer Verlag. https://doi.org/10.1007/11867661_54
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