Tracer kinetic model-driven registration for dynamic contrast enhanced MRI time series

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Abstract

Motion during time-series data acquisition causes model-fitting errors in quantitative dynamic contrast-enhanced (DCE) MRI studies. Motion correction techniques using conventional registration cost functions may produce biased results because they were not designed to deal with the time-varying information content due to contrast enhancement. We present a locally-controlled, 3D translational registration process driven by tracer kinetic modeling that successfully registers abdominal DCE-MRI data at high temporal resolution and compare this method to a similar approach based on registration to the time series mean image in data from 8 patients. When the registration is driven by an appropriate model, we find significant improvements in model-fitting. Also, model-driven registration influences parameter estimates and reduces repeat study variability in measurements of blood volume. © Springer-Verlag Berlin Heidelberg 2005.

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Buonaccorsi, G. A., Roberts, C., Cheung, S., Watson, Y., Davies, K., Jackson, A., … Parker, G. J. M. (2005). Tracer kinetic model-driven registration for dynamic contrast enhanced MRI time series. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3749 LNCS, pp. 91–98). https://doi.org/10.1007/11566465_12

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