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Abstract #0169

Automatic Segmentation of the Venous Vessel Network Based on Quantitative Susceptibility Maps and its Application to Investigate Blood Oxygenation

Barthlemy Serres 1 , Andreas Deistung 1 , Andreas Schfer 2 , Marek Kocinski 3 , Andrzej Materka 3 , and Jrgen Reichenbach 1

1 Medical Physics Group, Institute for Diagnosis and Interventional Radiology, University Hospital Jena - Friedrich Schiller University Jena, Jena, Germany, 2 Max Plank Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 3 University of Lodz, Lodz, Poland

A common method to assess the venous blood vessel network in high-spatial detail is susceptibility weighted imaging(SWI). However, contrast on susceptibility weighted images may be non-local and there is a complex relationship between the orientation of venous vessel axis and the main magnetic field. To overcome this issue quantitative susceptibility mapping (QSM), a novel technique that enables conversion of gradient-echo phase images into maps of the magnetic susceptibility in vivo, can be applied. Due to its quantitative nature, QSM also offers the possibility to estimate oxygen saturation within blood vessels. In this contribution, we present an approach for automatic segmentation of venous vessels based on quantitative susceptibility maps to produce highly accurate 3D reconstructions of the cerebral venous network. This approach is also used to investigate blood oxygenation within the venous network.

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