Purpose: To improve the performance of magnetic resonance imaging (MRI) based venous vessel segmentation algorithms by examining the impact of different imaging parameters, reconstruction techniques and post-processing techniques. Background: The deoxygenated haemoglobin in venous blood has a distinct magnetic susceptibility, which manifests in the phase of MRI data. The phase-contrast is sensitive to sequence parameters and reconstruction. Post-processing techniques are used to enhance the contrast prior to segmenting the vasculature. Method: Each combination of MRI sequence, reconstruction technique, and post-processing algorithm was investigated. Sequences included single echo and dual echo. Reconstruction techniques included GRAPPA1 and CSense2 . Post-processing techniques included high-pass filtering, rod-like filters3 , susceptibility-weighted imaging4 and vesselness filters5 . Each unique combination of sequence, reconstruction technique and post-processing technique (a pipeline) was tuned (reconstruction and post-processing parameters) to optimise performance and the resultant image displayed as a minimum intensity projection (mIP). The performance of each pipeline, for a small set of vessels with different orientations and diameters, was visually assessed and compared objectively using the signal-to-noise ratio in the mIP visualisation. Results: The selection of pipeline components had a strong effect upon vessel appearance. Vessel visibility was dependent on vessel size, orientation and location in addition to being sensitive to pipeline components. No strong relationship between number of tuneable parameters and vessel contrast was found. Dual echo sequences consistently outperformed single echo sequences. Conclusion: This investigation provided a guide for component selection when imaging cerebro-vasculature and suggested optimal contrast was dependent upon the size, orientation and location of the target vessels.