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Nowadays, objective protocols and criteria for the monitoring of phantoms failures are still lacking in literature, despite their technical limitations. In such a context, the present work aims at providing an improvement of a previously proposed method for the Doppler flow phantom failures detection. Such failures were classified as low frequency oscillations, high velocity pulses and velocity drifts. The novel objective method, named EMoDICA-STFT, is based on the combined application of the Empirical Mode Decomposition (EMD), Independent Component Analysis (ICA) and Short Time Fourier Transform (STFT) techniques on Pulsed Wave (PW) Doppler spectrograms. After a first series of simulations and the determination of adaptive thresholds, phantom failures were detected on real PW spectrograms through the EMoDICA-STFT method. Data were acquired from two flow phantom models set at five flow regimes, through a single ultrasound (US) diagnostic system equipped with a linear, a convex and a phased array probe, as well as with two configuration settings. Despite the promising outcomes, further studies should be carried out on a greater number of Doppler phantoms and US systems as well as including an in-depth investigation of the proposed method uncertainty.

Doppler flow phantom failure detection by combining empirical mode decomposition and independent component analysis with short time Fourier transform