In many applications, there is a great demand for reliable, small, and low-cost three-dimensional imaging systems. Promising systems for applications such as automotive applications as well as safe human robotic collaboration are light detection and ranging (lidar) systems based on the direct time-of-flight principle. Especially for covering a large field of view or long-range capabilities, the previously used polygon-scanners are replaced by microelectromechanical systems (MEMS)-scanners. A more recent development is to replace the typically used avalanche photodiodes with single-photon avalanche diodes (SPADs). The combination of both technologies into a MEMS-based SPAD lidar system promises a significant performance increase and cost reduction compared with other approaches. To distinguish between signal and background/noise photons, SPAD-based detectors have to form a histogram by accumulating multiple time-resolved measurements. In this article, a signal and data processing method is proposed, which considers the time-dependent scanning trajectory of the MEMS-scanner during the histogram formation. Based on known reconstruction processes used in stereo vision setups, an estimate for an accumulated time-resolved measurement is derived, which allows to classify it as signal or noise. In addition to the theoretical derivation of the signal and data processing, an implementation is experimentally verified in a proof-of-concept MEMS-based SPAD lidar system.