Frequency Domain Pseudo-color to Enhance Ultrasound Images
Why this work is in the frame
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Bibliographic record
Abstract
In digital image processing, image enhancement is employed to give a better look to an image. Color is one of the best ways to visually enhance an image. Pseudo-color refers to coloring an image by mapping gray scale values to a three dimensional color space. In this paper we used a pseudo-color technique in frequency domain to enhance ultrasound images. We used three different types of transforms to do this. These are the Fourier transform, Discrete Cosine transform and Walsh- Hadamard transform. After obtaining these pseudo-color images, we applied a high frequency emphasis filter or histogram stretch as a post process. In this paper we used a subjective study to compare images. First we compared pseudo-color images to their original monochrome images. Secondly, we compared all the three different types of transforms. Lastly, we compared the post processing techniques.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it