In MRI scans that are acquired in a slice-by-slice manner, patient motion during scanning can cause adjacent slices to overlap, resulting in duplicate coverage in some areas and missing coverage in others. Scans in which multiple slices are acquired simultaneously and interleaved with other sets of slices are particularly vulnerable because a single movement can result in the misalignment and overlap of many slices. Despite the fact that considerable data losses can occur even with few visible artifacts, this problem has received very little attention from MRI researchers. The primary goals of this paper are: (1) to raise awareness of the problem in the MRI community and (2) to present an efficient multiscale algorithm that accurately quantifies the amount of data loss. Validation of the algorithm's accuracy is performed on 200 scans with simulated patient motion so that the true amount of data loss is known for each scan. The motion parameters are chosen to simulate scans that have significant data loss (mean missing coverage = 14.39% of head volume, SD = 6.61%, range = 2.76–32.98%) but with few visual indications of the problem. The algorithm is shown to be very accurate, yielding estimates that differ from the true values by a mean of only 1.1% point (SD = 0.98 pt, range = 0.00–6.54 pt). The algorithm is also shown to be consistent and robust when tested on a large set of scans from a recent multiple sclerosis clinical trial.