Modified homomorphic wavelet based despeckling of medical ultrasound images
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Speckle noise suppression is a prerequisite task in order to maintain the diagnostic potential of ultrasound imaging. Among various despeckling methods, there exists a class which transforms the multiplicative speckle noise to the additive through a logarithmic transformation. In most of such studies, it is assumed that the samples of the multiplicative noise are mutually uncorrelated and they obey the Gaussian distribution. Present studies show that this assumption is oversimplified and it results in inadequate performance of speckle suppression. We introduce an adaptive preprocessing filter which de-correlates the samples of speckle noise and approximates its behavior to that of white Gaussian noise. The study also evaluates the performance of homomorphic wavelet despeckling (HWDS) with this adaptive preprocessing as the initial stage and demonstrates that the proposed adaptive preprocessing stage significantly improves the performance of HWDS both qualitatively and quantitatively.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it