Towards Real-time Simulation of Ultrasound Systems
Bibliographic record
Abstract
Diagnostic ultrasound is a non-invasive image modality commonly used to diagnose multiple diseases. Sonographers and physicians have to devote a substantial amount of time learning how the combination of the various parameters of the ultrasound system affects the resulting ultrasound information among its different modalities. The primary objective of this thesis is to create a mechanistic ultrasound simulation method that could achieve near real-time performance to teach and train sonographers and physicians. A major bottleneck for achieving real-time performance with available tools was the transducer field simulation method that uses the impulse response technique. To address this problem a new simulation approach was developed. This project was realized in a three-phase approach, specifically to simulate spectral Doppler. In first place, it was shown that is possible to mechanistically simulate the sample volume power distribution using a novel method based on an array of point sources to represent the transducer geometry. Secondly, by comparison with the Field II results, it was demonstrated that the time-domain signal could be closely reproduced using point sources. Finally, by treating the array of point sources as point receivers, the received signal was compared with the results from Field II, and again, good agreement was achieved. Simulation results were compared against the standard simulation method for a number of examples involving steady and pulsatile flow, for which the spectrograms were compared against Field II. Also presented are preliminary results obtained using the point source approach to simulate B-mode images. As well, methods are described for generating Doppler spectrograms from the results of computation fluid dynamics velocity fields obtained in realistic arterial geometrical models. It is pointed out that the successful simulation of the time domain signal opens the possibility for real-time simulation of other ultrasound modes.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".