Abstract #1787

Robust Arterial Input and Venous Output Function Detection for Automatic Processing in DSC-MRI

Matus Straka¹, Gregory W. Albers², Roland Bammer¹

¹Radiology, Stanford University, Stanford, CA, United States; ²Stroke Center, Stanford University Medical Center, Stanford, CA, United States

Routine acquisition of DSC-MRI PWI datasets highly benefits from full automated post-processing. Selection of arterial input and venous output function is a key step that ensures robustness and reliability of unsupervised processing. A novel method of AIF and VOF selection is proposed by means of tubular filtering and simple analysis of mean temporal signals. Weighting factors the favor arterial and venous signals, as well as vessel orientations are derived. As a result, robustness of AIF and VOF selection was improved.