A Preliminary Study on the Adaptive SNR Threshold Method for Depth of Penetration Measurements in Diagnostic Ultrasounds

Maximum depth of penetration (DOP) is among the most relevant parameters in quality assurance programs for Ultrasound (US) scanners. Nowadays, a generally-accepted protocol for DOP estimation is still awaited and, in common practice, DOP is visually assessed despite the low accuracy. To overcome the eye-based assessment subjectivity, automatic image analysis methods have been proposed in literature. The present work focuses on a novel automatic method, namely the adaptive Signal to Noise Ratio (SNR) threshold method (AdSTM), developed in the MATLAB environment, by comparing it with an existing automatic approach, namely the tangent threshold method (TTM), and the mean judgment of eight observers (naked eye method). The three investigated methods were applied on data acquired from four US scanners for general purpose imaging, equipped with linear, convex, and vector array probes. Tests were carried out in two different configuration settings (raw scanner and default preset working conditions). AdSTM outcomes were tested by means of Monte Carlo Simulations. Most of measurement results were compatible despite the fact that the AdSTM seemed to be more sensitive and faster than the TTM. The results analysis confirms the higher dispersion of the naked eye method in DOP assessment with respect to the proposed automatic methods.