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Abstract #4381

Arterial Input Function Selection in DSC-MRI of Brain Tumors Using Differential Evaluation Clustering Method

Hossein Rahim Zadeh1, Anahita Fathi Kazerooni1,2, Mohammad Reza Deevband3, and Hamidreza Saligheh Rad1

1Quantitative MR Imaging and Spectroscopy Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran, 2Department of Medical Physics and Biomedical Engineering, Tehran University of Medical Sciences, Tehran, Iran, 3Shahid Beheshti University of Medical Sciences, Tehran, Iran

Proper arterial input function (AIF) selection is a critical step for accurate quantification of dynamic susceptibility contrast enhanced (DSC) MRI in brain tumor patients. In this study, we have employed differential evaluation (DE) clustering method on processed perfusion images for accurate AIF selection. The procedure consists of two main steps: preprocessing for eliminating non-arterial curves including tissue, noisy and those contaminated with partial volume effects; and AIF selection using DE clustering method. The performance of this clustering method was compared to K-means and Hierarchical Clustering techniques and the results show the superiority of the proposed approach for accurate AIF selection.

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