Satisfactory image quality is essential to accurately assess brain volume using automated methods for evaluating neurodegenerative diseases. Variations in image quality may cause volume estimation errors hard to distinguish from disease-induced changes. We studied the relationship between brain volume estimations and image quality metrics in a scan-rescan study. Two segmentation methods were used to quantify brain volume in FLAIR and MPRAGE images. Volume estimations on MPRAGE varied less with hardware, compared to the estimations on FLAIR. We found a significant correlation between hardware and several image quality metrics, suggesting that these can be used to render volume estimations more hardware-independent.