SU‐F‐I‐19: MRI Positive Contrast Visualization of Prostate Brachytherapy Seeds Using An Integrated Laplacian‐Based Phase Processing
Bibliographic record
Abstract
Purpose: To propose a new method that provides a positive contrast visualization of the prostate brachytherapy seeds using the phase information from MR images. Additionally, the feasibility of using the processed phase information to distinguish seeds from calcifications is explored. Methods: A gel phantom was constructed using 2% agar dissolved in 1 L of distilled water. Contrast agents were added to adjust the relaxation times. Four iodine‐125 (Eckert & Ziegler SML86999) dummy seeds were placed at different orientations with respect to the main magnetic field (B0). Calcifications were obtained from a sheep femur cortical bone due to its close similarity to human bone tissue composition. Five samples of calcifications were shaped into different dimensions with lengths ranging between 1.2 – 6.1 mm.MR imaging was performed on a 3T Philips Achieva using an 8‐channel head coil. Eight images were acquired at eight echo‐times using a multi‐gradient echo sequence. Spatial resolution was 0.7 × 0.7 × 2 mm, TR/TE/dTE = 20.0/2.3/2.3 ms and BW = 541 Hz/pixel. Complex images were acquired and fed into a two‐step processing pipeline: the first includes phase unwrapping and background phase removal using Laplacian operator (Wei et al. 2013). The second step applies a specific phase mask on the resulting tissue phase from the first step to provide the desired positive contrast of the seeds and to, potentially, differentiate them from the calcifications. Results: The phase‐processing was performed in less than 30 seconds. The proposed method has successfully resulted in a positive contrast of the brachytherapy seeds. Additionally, the final processed phase image showed difference between the appearance of seeds and calcifications. However, the shape of the seeds was slightly distorted compared to the original dimensions. Conclusion: It is feasible to provide a positive contrast of the seeds from MR images using Laplacian operator‐based phase processing.
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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 | 0.001 |
| 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".