Limited value of ultrasound assessment in patients with poor outcome after carpal tunnel release surgerys

[EN] OBJECTIVE: To determine the value of ultrasonography in the assessment of patients with idiopathic carpal tunnel syndrome (CTS) and poor outcome after carpal tunnel release. METHODS: A total of 88 consecutive patients with CTS (104 hands) underwent open surgical release of the median nerve. Ultrasound (US) examination was performed blind to any patient's data. The median nerve area at tunnel inlet and outlet, the retinaculum distance, and the flattening ratio were measured. The main outcome variable was the patient's overall satisfaction using a five-point Likert scale (1 = worse, 2 = no change, 3 = slightly better, 4 = much better, 5 = cured) at 3 months postoperatively. Pre- and postoperative ultrasonographic findings in relation to clinical outcome were analysed. RESULTS: Improvement (scores 4 or 5 on the Likert scale) was recorded in 75 hands (72%). After carpal tunnel release, the cross-sectional area at tunnel inlet decreased from a mean of 14.2 to 13.3 mm2 in the group with clinical improvement and also from a mean of 12.5 to 11.6 mm2 in the group with no change or slight improvement. No significant changes in the cross-sectional area at tunnel outlet, retinaculum distance, and flattening ratio were observed. CONCLUSION: Reduction of the median nerve cross-sectional area at tunnel inlet at 3 months after carpal tunnel release was similar in patients reporting cure or great improvement and in those with slight or no improvement. Ultrasonography is of limited value in assessment of patients with poor outcome after median nerve release.

Variational second order flow estimation for PIV sequences

[EN] We present in this paper a variational approach to accurately estimate simultaneously the velocity field and its derivatives directly from PIV image sequences. Our method differs from other techniques that have been presented in the literature in the fact that the energy minimization used to estimate the particles motion depends on a second order Taylor development of the flow. In this way, we are not only able to compute the motion vector field, but we also obtain an accurate estimation of their derivatives. Hence, we avoid the use of numerical schemes to compute the derivatives from the estimated flow that usually yield to numerical amplification of the inherent uncertainty on the estimated flow. The performance of our approach is illustrated with the estimation of the motion vector field and the vorticity on both synthetic and real PIV datasets.

An evolutive approach for smile recognition in video sequences

Facial expression recognition is one of the most challenging research areas in the image recognition ¯eld and has been actively studied since the 70's. For instance, smile recognition has been studied due to the fact that it is considered an important facial expression in human communication, it is therefore likely useful for human–machine interaction. Moreover, if a smile can be detected and also its intensity estimated, it will raise the possibility of new applications in the future