Mitigation of Motion Artifacts in Handheld Laser Speckle Contrast Imaging Illustrated on Psoriasis Lesions

Background
: Handheld laser speckle contrast imaging (LSCI) is crucial in clinical settings, but motion artifacts (MA) can compromise perfusion image reliability. Current prevention and suppression methods are often impractical or complex. Machine vision techniques, promising in medical imaging, could improve signal quality, but their use in suppressing MA is still unexplored.
Objective
: We propose an innovative method based on linear regression for MA correction (MAC) in LSCI and validate it in vivo.
Methods
: We performed paired handheld and mounted LSCI measurements on 14 subjects with psoriasis using the previously validated handheld perfusion imager (HAPI). By marking lesion boundaries for clinical purposes, the HAPI used a monochromatic camera for both speckle imaging and motion detection, simplifying hardware requirements. Accurate estimation of relative displacements between the test object and LSCI probe allowed us to apply MAC to the perfusion images.
Results
: Local perfusion values correlated with applied speed were used to calculate and correct MA. The difference between mean perfusion in handheld and mounted modes after MAC significantly decreased (median error 14.2 perfusion units (p.u.) on lesions before correction (
$p< 0.0005$
) and 0.5 p.u. after correction (
$p=0.2$
)).
Conclusion
: The findings provide evidence for robust handheld LSCI and validate the MA technique in psoriasis case. Of the two causes of MA-onsurface speeds and wavefront tilt-we address the former and correct mean perfusion, assuming constant temporal perfusion at each location.
Significance
: We describe a practical, non-contact, marker-free technique for reliable handheld perfusion imaging, supporting further clinical translation in plastic surgery and burns.