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Abstract #0694

Artery-Vein Segmentation in Non-Contrast-Enhanced Flow-Independent 3D Peripheral Angiography

Serena Y. Yeung1, Kie Tae Kwon1, Bob S. Hu1, 2, Dwight G. Nishimura1

1Electrical Engineering, Stanford University, Stanford, CA, United States; 2Palo Alto Medical Foundation, Palo Alto, CA, United States

Magnetization-prepared 3D SSFP sequences have shown promise for non-contrast-enhanced flow-independent angiography (FIA), where intrinsic tissue parameters such as T1, T2, and chemical shifts are exploited to generate stable vessel contrast even under slow flow conditions. However, an important challenge with this approach is sufficient artery-vein contrast, which is crucial for artery visualization and the diagnosis of arterial disease. In this work, we apply the Maximally Stable Extremal Regions (MSER) detector and k-means clustering to perform unsupervised segmentation and removal of the femoral veins in 3D FIA datasets of the lower extremities.