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Deterministic Arterial Input Function selection in DCE-MRI for automation of quantitative perfusion calculation of
Christian Tönnes1, Sonja Janssen2, Alena-Kathrin Golla1
1Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany.
Abstract:
Development of a deterministic algorithm for automated detection of the Arterial Input Function (AIF) in DCE-MRI of colorectal cancer. Using a filter pipeline to determine the AIF region of interest. Comparison to algorithms from literature with mean squared error and quantitative perfusion parameter Ktrans. The AIF found by our algorithm has a lower mean squared error (0.0022 ± 0.0021) in reference to the manual annotation than comparable algorithms. The error of Ktrans (21.52 ± 17.2%) is lower than that of other algorithms. Our algorithm generates reproducible results and thus supports a robust and comparable perfusion analysis.
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