Real-Time Hand-Held Ultrasound Medical-Imaging Device Based on a New Digital Quadrature Demodulation Processor
Bibliographic record
Abstract
A fully hardware-based real-time digital wideband quadrature demodulation processor based on the Hilbert transform is proposed to process ultrasound radio frequency signals. The presented architecture combines 2 finite impulse response (FIR) filters to process in-phase and quadrature signals and includes a piecewise linear approximation architecture that performs the required square root operations. The proposed implementation enables flexibility to support different transducers with its ability to load on-the-fly different FIR filter coefficient sets. The complexity and accuracy of the demodulator processor are analyzed with simulated RF data; a normalized residual sum-of-squares cost function is used for comparison with the Matlab Hilbert function. Three implementations are integrated into a hand-held ultrasound system for experimental accuracy and performance evaluation. Real-time images were acquired from a reference phantom, demonstrating the feasibility of using the presented architecture to perform real-time digital quadrature demodulation of ultrasonic signal echoes. Experimental results show that the implementation, using only 2942 slices and 3 dedicated digital multipliers of a low-cost and low-power field-programmable gate array (FPGA) is accurate relative to a comparable software- based system; axial and lateral resolution of 1 mm and 2 mm, respectively, were obtained with a 12-mm piezoelectric transducer without postprocessing. Because the processing and sampling rates are the same, high-frequency ultrasound signals can be processed as well. For a 15-frame-per-second display, the hand-held ultrasonic imaging-processing core (FPGA, memory) requires only 45 mW (dynamic) when using a 5-MHz single-element piezoelectric transducer.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".