A novel method for tracking of muscle thickness changes in ultrasound image sequences

Ultrasonography is frequently used to estimate changes in muscle thickness in both static and dynamic contractions. Conventionally, most such measurements are conducted by manually analyzing ultrasound images. This manual approach is time consuming, subjective, prone to error, and not suitable for measuring dynamic change. In this study, we developed an automated tracking method based on an optical flow algorithm using an affine motion model. The goal of the study was to evaluate the performance of the proposed method by comparing it with the manual approach. Real-time B-mode ultrasound was used to exam the rectus femoris muscle during voluntary contraction. The manual and automated methods were compared by linear regression and Bland-Altman analysis. The findings showed that the proposed method was in good agreement with the manual approach.