A 256 x 256 2-D array transducer with row-column addressing for 3-D rectilinear imaging
Bibliographic record
Abstract
We present simulation and experimental results from a 5-MHz, 256 x 256 2-D (65,536 elements, 38.4 x 38.4 mm) 2-D array transducer with row-column addressing. The main benefits of this design are a reduced number of interconnects, a modified transmit/receive switching scheme with a simple diode circuit, and an ability to perform volumetric imaging of targets near the transducer with transmit beamforming in azimuth and receive beamforming in elevation. The final dimensions of the transducer were 38.4 mm x 38.4 mm x 300 microm. After a row-column transducer was prototyped, the series resonance impedance was 104 Omega at 5.4 MHz. The measured -6 dB fractional bandwidth was 53% with a center frequency of 5.3 MHz. The SNR at the transmit focus was measured to be 30 dB. At 5 MHz, the average nearest neighbor crosstalk was -25 dB. In this paper, we present 3-D images of both 5 pairs of nylon wires embedded in a clear gelatin phantom and an 8 mm diameter cylindrical anechoic cyst phantom acquired from a 256 x 256 2-D array transducer made from a 1-3 composite. We display the azimuth and elevation B-scans as well as the C-scan for each image. The cross-section of the wires is visible in the azimuth B-scan, and the long axes can be seen in the elevation B-scan and C-scans. The pair of wires with 1-mm axial separation is discernible in the elevational B-scan. When a single wire from the wire target phantom was used, the measured lateral beamwidth was 0.68 mm and 0.70 mm at 30 mm depth in transmit beamforming and receive beamforming, respectively, compared with the simulated beamwidth of 0.55 mm. The cross-section of the cyst is visible in the azimuth B-scan whereas the long axes can be seen as a rectangle in the elevation B-scan and C-scans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".