Three-dimensional visualization and thickness estimation of aortic valve cusps using high-frequency ultrasound
Bibliographic record
Abstract
High-frequency ultrasound techniques are introduced for three-dimensional imaging and thickness estimation of fresh heart valve cusps. Images of porcine aortic valve specimens were acquired within a 12 x 8 x 8 mm3 volume using a VisualSonics VS40 micro-imaging system operating at a 40 MHz centre frequency. Two image volumes were obtained from each of six left coronary cusps. One volume was acquired with the specimen submerged in distilled water and the second volume was acquired through either Hanks physiologic solution or coronary perfusion solution (CPS). The fibrosa, spongiosa and ventricularis were most readily distinguished when the specimen was imaged in distilled water. Colour thickness maps were computed from B-mode image data, and the mean and standard deviations of the thickness were determined for each cusp. In 11 of 12 trials, the image analysis algorithm yielded valid thickness estimates over greater than 98% of the region examined. Mean thickness estimates obtained with specimens submerged in Hanks solution or CPS ranged from 0.66 to 1.03 mm, and submersion in distilled water increased the mean thickness by 20-40%. This observation suggests that the cusps osmotically absorbed water. Information provided by high-frequency ultrasound is expected be valuable for characterizing the morphological properties of heart valves.
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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) | 0.000 | 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) | 0.000 | 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".