Automatic Detection of Abrupt Patient Motion in SPECT Data Acquisition

Due to the long imaging times in SPECT, patient motion is inevitable and constitutes a serious problem for any reconstruction algorithm. The measured inconsistent projection data leads to reconstruction artefacts which can significantly affect the diagnostic accuracy of SPECT, if not corrected. Among the most promising attempts for addressing this cause of artefacts, is the so-called data-driven motion correction methodology. To use this approach it is necessary to automatically detect patient motion and to subdivide the acquired data in projection sets accordingly. In this note, we propose three different schemes for automatically detecting patient motion. All methods were tested on 3D academic examples with different rigid motions, motion times, and camera systems. On the whole, every method was tested with approximately 400 to 600 test cases. One of the proposed new methods does show promising results.