Although human cerebrovascular system is the basis of most non-invasive measures of neural activity, its structure is poorly understood owing to the difficulty in identifying, segmenting and separating venous and arterial vessels. To resolve this, we used Susceptibility Weighting Imaging (SWI) and Magnetic Resonance Angiography Time-of-Flight (MRA-TOF) to develop a probabilistic template of vascular architecture in the MNI space using an iterative back projection approach. This template is then paired with an anatomical atlas illustrates how some grey-matter areas are more vascularized than others. This could be the first steps toward a region-based vascular regression tool for the analysis hemodynamic-based measures of brain activity, such as fMRI.
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