# Requirements and Hardware Limitations of High-Frame-Rate 3-D Ultrasound Imaging Systems
## 5 Conclusions  
Relevant metrics for the reception stage of an ultrasound system have been identified in Section 2. The results in Table 1 point out that the most critical issues are related to the number of MAC/s operations needed by beamforming, and to the corresponding output data rate. Specifically, for the HFR imaging modalities, more than 1.3 TMAC/s, and data rates as high as 5000 MB/s can be yielded. Such demanding requirements strongly influence both the hardware and the digital architecture of a scanner. Typically, hardware-based scanners use modular architectures [11; 43], in which each module manages part of the channels to fit the real-time constraints. Modularity, anyway, also increases the complexity of the system, and special attention must be taken to efficiently distribute the computational and data transfer loads. If this need is not respected, the benefits can be nullified by the bottlenecks that may occur. For example, for HFR 3-D imaging, the amount of beamformed data can be much higher than the amount of raw data (see the examples 3-D PW 256 and 3-D PW 1024 in Table 1): correspondingly, the overall system performance is easily limited by the communication bus. For the ULA-OP 256, a representative hardware-based scanner, excessively high PRF values determined system instability while performing real-time high frame rate imaging. This could be due to the available resources and their interconnection topology, which in turn caused beamforming limitations, data transfer bottlenecks, or a DSP computational power bottleneck. Taking advantage of the ring topology over the star topology allowed overcoming the data transfer bottleneck, obtaining up to 4400 frames/s, and more than 1000 compounded  
Figure 4: Sample screenshots of the real-time user interface of ULA-OP 256 during phantom investigation. Top panels: sample images obtained with diverging wave transmission (DW1) from 128 (Experiment I) and 256 (Experiment II) elements of the 2-D Vermon probe. Bottom panels: bi-plane (Experiment IV) transverse (**left**) and longitudinal (**right**) “compounded” views, simultaneously obtained through the transmission of five diverging waves (DW5). frames/s. This is, to the best of our knowledge, the top level HFR performance achieved by an open scanner in real-time. Experiment V also highlighted the requirements and capabilities of a real-time volumetric imaging system. For a small (960 lines) volume, the ULA-OP 256 enabled a maximum volume rate, FR\({}_{\text{MAX}}\), of 510 Hz in DW1 and 140 Hz in DW5 mode, respectively. Such volume rates are high enough for morphological imaging and enable the processing by methods based on contour or speckle tracking algorithms with high temporal resolution. Furthermore, it is worth highlighting that the high sampling frequency (39.06 MHz) used in the experiments are high enough to immediately transfer the results shown in Table 3 to probes operating at up to 9.75 MHz. The results in Table 3 point out that concerning the new ring topology, the remaining bottleneck is, in most cases, represented by the parallel beamforming output rate. However, for all (DW1) cases, in which both B\({}_{\text{MC}}\) and B\({}_{\text{BF}}\) are lower than the achievable limits, the bottleneck is probably related to the DSP's inability to sustain the requested working load. The possible drawbacks of this topology can also be highlighted. First, data handling and synchronization are surely more complex with respect to the star configuration, especially when many boards are involved. Furthermore, this topology's results are convenient only in those cases where the performance of a board acting as a central node is limited by a saturation of input transfer bandwidth. This topology in fact cannot increase the parallelization capabilities of a system but can be useful to solve localized and unbalanced transfer bandwidths that limit the computational capacity of a scanner.