Abstract #4726

Performance of Automatic Cerebral Arterial Segmentation of MRA Images Improves in Patients with Anemia and Sickle Cell Disease Compared with Healthy Volunteers.

Alexander Saunders¹, John C. Wood², and Matthew Borzage^3,4

¹Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States, ²Division of Cardiology, Children's Hospital Los Angeles, Los Angeles, CA, United States, ³Division of Neonatology, Children's Hospital Los Angeles, Los Angeles, CA, United States, ⁴Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States

Sickle cell disease (SCD) and chronic anemia cause morphological abnormalities in the cerebral arterial vasculature that are observable using time-of-flight magnetic resonance angiography (MRA). We seek to evaluate the accuracy of automatic vessel segmentation algorithms in extracting vessel data from these images for further analysis. Five segmentation algorithms were applied to three MRA images (one control, one anemic, and one SCD patient) and performance was measured against manually segmented ground truth data. We found that automatic segmentation performs better in anemic and SCD patients over healthy controls.

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