Fast Orthogonal Row–Column Electronic Scanning Experiments and Comparisons
Bibliographic record
Abstract
Three-dimensional ultrasound imaging presents technical challenges of addressing large numbers of elements in 2D array transducers. Top-Orthogonal to Bottom Electrode (TOBE) 2D transducer arrays can simplify addressing but typical imaging methods with such arrays enable only one-way focusing in azimuth and elevation. Here experimental results are reported for the Fast Orthogonal Row-Column Electronic Scanning (FORCES) imaging scheme implemented on a 64 ×64 element bias-sensitive electrostrictive relaxor TOBE array. The FORCES imaging scheme involves transmitting along rows to form an elevational transmit focus, while biasing columns with bias patterns selected from a Hadamard matrix. Channel data from columns is received and decoded for synthetic aperture beamforming in azimuth. This scheme offers two-way azimuthal focusing. Volumetric imaging experiments were conducted using wire phantoms as well as on rat hearts using two different TOBE imaging schemes: Scheme 1 (transmit focusing in elevation and receive focusing in azimuth) and FORCES. Wire phantom experiments at a depth of 2 cm showed an azimuthal resolution of 0.42 mm and 0.31 mm with Scheme 1 and FORCES, respectively. We also compared the elevational imaging performance of these imaging schemes with a mechanically scanned linear array. The FORCES imaging displayed an elevational resolution of 0.46 mm at a depth of 2 cm and the linear array an elevational resolution of 0.72 cm. The novel TOBE array architecture and FORCES imaging scheme thus enable high-quality 3D ultrasound imaging using only row-column addressing and bias control, and may prove an enabling technology for many future 3D imaging platforms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".