Time-scale detection of microemboli in flowing blood with Doppler ultrasound.

Small formed elements and gas bubbles in flowing blood, called microemboli, can be detected using Doppler ultrasound. In this application, a pulsed constant-frequency ultrasound signal insonates a volume of blood in the middle cerebral artery, and microemboli moving through its sample volume produce a Doppler-shifted transient reflection. Current detection methods include searching for these transients in a short-time Fourier transform (STFT) of the reflected signal. However, since the embolus transit time through the Doppler sample volume is inversely proportional to the embolus velocity (Doppler-shift frequency), a matched-filter detector should in principle use a wavelet transform, rather than a short-time Fourier transform, for optimal results. Closer examination of the Doppler shift signals usually shows a chirping behavior apparently due to acceleration or deceleration of the emboli during their transit through the Doppler sample volume. These variations imply that a linear wavelet detector is not optimal. We apply linear and quadratic time-frequency and time-scale detectors to a set of noise-corrupted embolus data. Our results show improvements of about 1 dB using the time-scale detectors versus an STFT-based detector signifying that embolus detection is best approached as a time-scale problem. A time-scale-chirp detector is also applied and is found to have the overall best performance by about 0.5-0.7 dB while coming fairly close (about 0.75 dB) to a theoretical upper bound.