Advantage of sampling density weighted apodization over postacquisition filtering apodization for sodium MRI of the human brain
Bibliographic record
Abstract
For sodium imaging of the human brain, Gibbs' ringing can degrade image appearance and confound image analysis; k-space filtering is generally required. In this work, the signal to noise ratio (SNR) advantage of sampling density weighted apodization (SDWA) over uniform k-space sampling with postacquisition filtering apodization (UPFA) is quantified for sodium three-dimensional (3D) twisted projection imaging (TPI) of the human brain. A direct comparison was conducted with the creation of two TPI projection data sets (each with an equal number of projections of equal length): one generating uniform sampling density, and the other a "generalized Hamming" sampling density that conformed to 3D-TPI constraints for full k-space sampling. In this work it is shown theoretically, and then experimentally with sodium imaging of the human brain, that an SNR advantage of 17% is associated with the use of SDWA over UPFA for the filter presented, along with a significant noise-coloring benefit.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".