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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