Bibliographic record
Abstract
Current technology used to diagnose hearing disorders is limited. This is mostly due to\nthe fact that the auditory structures are very small and not easily accessible with existing\nimaging technologies. The objective of this dissertation was to investigate the potential\nof high-frequency ultrasound as a tool for exploring the anatomy of the auditory system.\nThree studies were conducted in order to demonstrate the feasibility of high-frequency\nultrasound as a diagnostic technology for hearing disorders.\nIn the first study, an in-house developed 50 MHz annular array-based ultrasound system\nwas used to provide ex-vivo images of auditory structures in cadaveric temporal bones. It\nwas shown that the spatial resolution was sufficient to visualize a high level of detail of the ossicular bones of the middle ear as well as intra-cochlear structures of the inner ear. In the second study, a 50 MHz 1.26? pitch phased array ultrasound transducer was designed for imaging intra-cochlear structures through the round window membrane. As this element pitch results in large grating lobe artifacts, novel transmit beamforming techniques were developed to suppress grating lobes resulting from this large-pitch array. Theoretical techniques using the impulse-response simulation method and experimental verification using high-frequency linear array ultrasound system (Vevo 2100, VisualSonics, Canada) showed that these techniques were able to suppress grating lobe levels up to 40 dB. In the third study, a needle mounted 45 MHz single-element ultrasound probe was fabricated in order to measure the vibrations of intra-cochlear structures on human cadavers. Basilar membrane velocimetry measurements were successfully performed using pulsed-wave Doppler ultrasound in the frequency range between 100 Hz-2 KHz. The measured velocity of the basilar membrane and the round window membrane showed that the middle ear resonance frequency near 1 KHz was present over multiple temporal bones. This is the first work that has explored the human auditory system with high resolution ultrasonic visualization and Doppler velocimetry.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".