Bilinear Models for Spatio-Temporal Point Distribution Analysis
International Journal of Computer Vision
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Biomedical imaging has become ubiquitous in both basic research and the clinical context. Technology advances and the resulting multitude of imaging modalities have led to a sharp rise in the quantity and quality of such images. In addition, computational models are increasingly used to study biological processes involving spatio-temporal changes in organisms, e.g. the growth of a tumor, and models and images are extensively described in natural language, for example in research publications and patient records. Together this leads to a major spatio-temporal data and model integration challenge for the next generation of biomedical and eHealth information systems. In this paper, we discuss a pilot study of volumetric data integration in the context of the Virtual Physiological Human initiative. Three types of spatio-temporal biomedical data sources are briefly introduced and the motivation for their integration presented in use case scenarios. The sources include a computational model of the human heart from the heart physiome project, a statistical atlas of human heart, and a 3D framework for the developing mouse embryo. We report on our experiences of integrating these resources and discuss the wider requirements of volumetric data integration in the biomedical research and eHealth domain.