Row-Column Beamformer for Fast Volumetric Imaging

A row-column beamformation algorithm is presented, which yields the output from the conventional delay-and-sum algorithm while reducing the number of operations by order of magnitude. The proposed method uses that in a row-column synthetic aperture sequence, the low-resolution volumes (LRV) have approximately constant image values along the elevation axis. It is, thus, possible to reconstruct the entire LRV from a single cross-section by modeling the positions with constant image values. As such, the proposed method consists of two stages. The first stage beamforms a low-resolution image per emission using the conventional approach. The second stage reconstructs the LRVs with one interpolation per voxel. Lastly, a high-resolution volume (HRV) is obtained by summing the LRVs across all emissions. The proposed algorithm was evaluated on measured data acquired using a 6 MHz 128+128 Vermon row-column probe and a Verasonics Vantage system. The proposed method beamformed a $100 \times 100 \times 200$ HRV consisting of 48 LRVs at a volume rate of 38 Hz. This was 9.23 times faster than a published GPU implementation of the conventional approach and real-time volumetric beamformation was achieved with a pulse repetition frequency of up to 1805 Hz. The output from the conventional and proposed beamformer was visually indistinguishable, and their point spread function's width heccurate interpolation requiright at -6 dB and -20 dB deviated less than 0.5%. This demonstrates that the number of operations of the conventional row-column beamformer can be significantly reduced with a negligible impact on image quality.</p

Comparison of 2D SURE and 3D CT imaging of cortical vessels in a rat kidney

SUper-Resolution ultrasound imaging using the Erythrocytes (SURE) can visualize blood vessels at about 25 to 50 µm resolution, but validation is required to assess how accurately the vasculature and its morphology are represented. Previous work compared ultrasound imaging to maximum intensity projections (MIP) of micro-CT volumes at an insufficient voxel size of 22.6 µm. Here, a 5 µm voxel size micro-CT volume of a cortical region in an excised rat kidney was acquired to test the hypothesis that blood vessels down to 50 µm in diameter are detected with SURE imaging. For the micro-CT volume, the blood vessels were segmented by an intensity threshold, and local thickness estimates were computed using expanding spheres within the segmentation mask. An affine registration between the SURE image and the micro-CT volume was manually defined, and a MIP of the microCT volume across 2 mm from the ultrasound imaging plane was computed for vessels with diameter estimates greater than 50 µm. The SURE image depicts 12 cortical radial vessels with high intensities and 9 dimmer cortical radial vessels. Notably, the 12 high intensity vessels are also depicted in the microCT projection, but 5 cortical radial vessels and 2 arcuate blood vessels are only visible in the SURE image. Of the faintly depicted cortical radial vessels, 5 vessels are not readily matched to vessels in the micro-CT projection. On the other hand, the microCT projection contains 6 cortical radial vessel segments and 2 arcuate blood vessels not depicted in the SURE image. These discrepancies in the comparison may arise from the challenging registration of the ultrasound focus beam and the micro-CT volume that is complicated further by the different states of the imaged tissue. Despite these challenges, SURE depicts most vessels at least down to 50 µm and even resolves parallel vessels not visible in the micro-CT projection, thus highlighting its clinical potential