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Vein segmentation using shape-based Markov Random Fields

The magnetic susceptibility of haemoglobin is modulated by oxygen saturation, providing a mechanism to non-invasively measure oxygen extraction fraction. When combined with perfusion techniques, quantitative susceptibility mapping facilitates regional measurement of cerebral metabolic rate of oxygen consumption. However, accurate measurement requires a complete vein map to measure anatomical variance in the metabolic demands of tissue. In this work we present a novel shape-based Markov Random Field technique to segmentation the cerebral veins that provides accurate and complete vein maps. The shape-based graph underpinning the model controls the spatial relationships between voxels and enforces cylindrical geometry, allowing increased sensitivity with accurate vein boundaries.