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Cardiovascular Risk Management by Advanced Medical Image Analysis (CARISMA)

Advances in medical imaging devices have drastically increased the capabilities to (non-invasively) study the human body; they not only provide detailed three- or four-dimensional morphological information on anatomy, but also on function and physiology. In addition, processes can increasingly be studied at a large range of spatial and temporal scales, thanks to – amongst others – the availability of a large number of custom-made biomarkers that enable the visualization of specific processes at the cellular and molecular level. These developments have a large potential to improve the understanding of disease processes, which in turn may lead to possibilities for drug discovery and development, improved diagnosis, prevention and early detection of disease, improved treatment monitoring, and improved treatment options, e.g. replacing conventional open surgery by image-guided, minimally invasive interventions.

With these advances, the sheer size, complexity, and heterogeneity of imaging data available for biomedical research and clinical practice have increased enormously. Consequently, the lack of adequate image processing techniques to analyze these data has become a main obstacle. There is an urgent need for solutions which enable the integrated analysis of complex, heterogeneous imaging data, which have been acquired with different imaging modalities and at different time points. This poses a formidable challenge, and requires a new generation of advanced image processing techniques, which can only be developed through an intense collaboration between the end users (clinicians), leading academic centers in the field of medical image analysis, and industry.

This programme aims to develop, validate and valorize a new generation of medical image analysis methods, which would enable the integrated analysis of heterogeneous and 4-D medical imaging data to improve disease detection, diagnosis, treatment, and prognosis. The focus of the programme will be on the generation of image-based technology that yields improved management of cardiovascular disease, an area with large societal relevance and economic potential.

Ontwikkelen, valideren en valoriseren van een nieuwe generatie analysemethoden voor medische beelden om aandoeningen eerder op te sporen, te diagnostiseren, te behandelen en het verloop ervan te voorspellen.
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The leader of this programme is J.H.C. Reiber, of the Leiden University Medical Center.

Bekijk alle projecten van dit programma

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Academisch Medisch Centrum
Three companies and one other university are invol
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