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Advanced Biomedical Engineering
Vol. 4 (2015) p. 73-79



Control of vasospasm is one of the most important problems in postoperative management after the occurrence of subarachnoid hemorrhage. Transcranial Doppler ultrasonography (TCD) is a non-invasive test that measures cerebral blood flow. However, high-intensity interference returned from the cranium causes estimation errors. A moving target indicator (MTI) filter is widely used to suppress the interference. The MTI filter suppresses only static target echoes, and hence the time-varying interference component caused by movement of the probe remains. To suppress the time-varying component, we apply spatial domain interferometry (SDI) with the Capon method to the MTI filtered signal. The method suppresses interference by minimizing the output power under the constraint condition of a constant response from a desired direction. The method requires estimation of the covariance matrix between signals received at the elements by averaging independent data. Conventional imagers based on SDI with the Capon method average the matrix in the temporal direction only in order to achieve high axial resolution. In TCD, both high temporal resolution and sufficient accuracy in measuring blood flow velocity are desired. Therefore, we propose a technique that averages the covariance matrix in both temporal and axial directions. We evaluated the performance of an SDI imager using the proposed technique in a simulation study, in which the array size was 12 elements, the transmit center frequency was 2.0 MHz, and the temporal and axial averaging lengths were 0.70 ms and 5.6 mm, respectively. The ratio of desired signal intensity to cranium interference intensity was −40 dB. The delay and sum (DAS) beamformer failed to estimate blood flow velocity of 1.0 m/s, and estimation error and standard deviation of 1.9 and 0.92 m/s, respectively. When the size for spatial averaging ranged from 25% to 50% of the number of elements, the proposed SDI beamformer succeeded to estimate the velocity of 1.0 m/s with estimation error and standard deviation of 0.044 m/s and 0.035 m/s, respectively. In contrast, the conventional SDI beamformer had estimation error and standard deviation of 0.17 and 0.25 m/s, respectively. These results indicate the effectiveness of the proposed technique in applying the SDI imaging method to TCD.

Copyright © 2015 Japanese Society for Medical and Biological Engineering

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