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Dark-field radiography of the human chest is a promising novel imaging technique with the potential of becoming a valuable tool for the early diagnosis of chronic obstructive pulmonary disease and other diseases of the lung. The large field-of-view needed for clinical purposes could recently be achieved by a scanning system. While this approach overcomes the limited availability of large area grating structures, it also results in a prolonged image acquisition time, leading to concomitant motion artifacts caused by intrathoracic movements (e.g. the heartbeat). Here we report on a motion artifact reduction algorithm for a dark-field X-ray scanning system, and its successful evaluation in a simulated chest phantom and human in vivo chest X-ray dark-field data. By partitioning the acquired data into virtual scans with shortened acquisition time, such motion artifacts may be reduced or even fully avoided. Our results …