Multi-level Analysis and Information Extraction Considerations for Validating 4D Models of Human Function
Recent research trends focus on how multiscale biomedical information can be modeled and transformed into knowledge, in order to lead to a less interfering but also more individualized diagnosis and therapy. In order to assess the clinical importance of models of human pathology (e.g. cancer), it is necessary to validate them with prior and post treatment clinical data which in turn requires the determination of the tumor size and shape with high resolution, accuracy and precision, as well as structural and physiological information. This paper discusses some of the most important image analysis challenges in order to define an optimal method for extracting more accurate and precise anatomical and functional information related to the underlying pathology, which can be used for initializing and validating models of pathophysiology as well as simulations/predictions of the response to therapeutical regimes.
KeywordsVirtual Physiological Human biomedical data analysis modeling
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