Improved tendon tracking using singular value decomposition clutter suppression

Ultrasound imaging is a real-time and high frame rate modality suitable for the analysis of tendon dynamics, e.g. for diagnosis of carpal tunnel syndrome. Tendon displacement quantification algorithms based on speckle tracking are sensitive to underestimation due to stationary clutter present in the tendon region. In this study we propose an improved speckle tracking method based on Singular Value Decomposition to suppress the stationary background. The method was optimized using image sequences from a human cadaver arm experiment. The ground truth displacement was found by tracking a metal marker inserted in the tendon. Various parameters involved in our method were optimized for best accuracy. Overall relative error of 3.2±2.3% was observed using our method compared to 7.4±4.8% using our previous speckle tracking method.

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