Duplex scanning using sparse data sequences

S. K. Møllenbach, Jørgen Arendt Jensen

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The velocity distribution in vessels can be displayed using duplex scanning where B-mode acquisitions are interspaced with the velocity data. This gives an image for orientation, but lowers the maximum detectable velocity by a factor of two. Other pulse sequences either omits the B-mode image or leaves gaps in the velocity data, which makes it difficult to output audio data. The near full velocity range can be maintained and B-mode images shown by using a sparse data sequence with velocity and B-mode samples intermixed. The B-mode samples are placed in a (sparse) periodical pattern, which makes reconstruction of the missing samples possible. The periodic pattern has the length T = M + A samples, where M are for B-mode and A for velocity estimation. The missing samples can now be reconstructed using a filter bank. One filter bank reconstructs one missing sample, so the number of filter banks corresponds to M. The number of sub filters in every filter bank is the same as A. Every sub filter contains fractional delay (FD) filter and an interpolation function. Many different sequences can be selected to adapt the B-mode frame rate needed. The drawback of the method is that the maximum velocity detectable is scaled by the factor A/T. The approach has been investigated using in vivo RF data from the Hepatic vein, Carotid artery and Aorta from a 33 year old healthy male. A B-K Medical 3535 ultrasound scanner has been used in Duplex mode with a BK 8556, 3.2 MHz linear array probe. The sampling frequency, the fprf and the resolution are 15 MHz, 3.5 kHz, and 12 bit sample (8 kHz and 16 bit for the Carotid artery). The resulting data contains 8000 RF lines with 128 samples at a depth of 45 mm for the vein and 50 mm for Aorta. Sparse sequences are constructed from the full data sequences to have both a reference sequence and sparse data sequences. After reconstruction the reference and the reconstructed spectrum are almost identical whe- - n characterized by the Signal to Noise Ratio (SNR). This is investigated and optimized by altering the number of filter coefficients, the implementation of the fractional delay filter, and the sparse sequence. The Hepatic vein data are processed with 5 filter coefficients, a FD filter implemented with a Knab window and sequence length T of 10 RF lines. By removing 7 lines the SNR is calculated to be 30 dB. When reconstruction over half the RF lines possible then to two spectograms can be acquired at the same time. The investigation of Aorta shows, that because the spectrum is wider, it puts some restrains on the selection of the sequence. The shortest sequence for getting a good spectrum consists of 7 lines, with one missing line (14.3%, SNR = 31.6 dB). Using sparse sequences both B-mode and velocity data can be acquired with only a modest degradation in maximum velocity. The reconstruction gives errors below the normal noise level in velocity data, and the full audio signal is precisely reconstructed from the data.
Original languageEnglish
Title of host publicationIEEE Ultrasonics Symposium, 2008. IUS 2008.
Publication date2008
ISBN (Print)978-1-4244-2428-3
Publication statusPublished - 2008
Event2008 IEEE International Ultrasonics Symposium - Beijing, China
Duration: 2 Nov 20085 Nov 2008


Conference2008 IEEE International Ultrasonics Symposium
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