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Abstract #0761

Fully Automated Generation of Arteriogram and Venogram Using Correlation and Pooled Covariance Matrix Analysis

Jiang Du1, Afshin Karami1, Yijing Wu2, Frank Korosec2, Thomas Grist2, Charles Mistretta2

1Radiology, University of California, San Diego, CA, United States; 2Medical Physics and Radiology, University of Wisconsin, Madison, WI, United States

Time-resolved CE-MRA provides contrast dynamics in the vasculature, which can be further used to separate arteries from veins. However, most of the segmentation algorithms require operator intervention. Furthermore, the contrast dynamics pattern may vary significantly within a large coronal imaging FOV due to delayed or asymmetric filling, or slow blood flow in the tortuous vessels. Correlation with single arterial and/or venous reference curves may result in misclassification. Here we present a fully automated region-specific segmentation algorithm for effective separation of arteries from veins based on cross correlation and pooled covariance matrix analysis.