Optimization of a retrospective technique for respiratory-gated high speed micro-CT of free-breathing rodents
Bibliographic record
Abstract
The objective of this study was to develop a technique for dynamic respiratory imaging using retrospectively gated high-speed micro-CT imaging of free-breathing mice. Free-breathing C57Bl6 mice were scanned using a dynamic micro-CT scanner, comprising a flat-panel detector mounted on a slip-ring gantry. Projection images were acquired over ten complete gantry rotations in 50 s, while monitoring the respiratory motion in synchrony with projection-image acquisition. Projection images belonging to a selected respiratory phase were retrospectively identified and used for 3D reconstruction. The effect of using fewer gantry rotations--which influences both image quality and the ability to quantify respiratory function--was evaluated. Images reconstructed using unique projections from six or more gantry rotations produced acceptable images for quantitative analysis of lung volume, CT density, functional residual capacity and tidal volume. The functional residual capacity (0.15 +/- 0.03 mL) and tidal volumes (0.08 +/- 0.03 mL) measured in this study agree with previously reported measurements made using prospectively gated micro-CT and at higher resolution (150 microm versus 90 microm voxel spacing). Retrospectively gated micro-CT imaging of free-breathing mice enables quantitative dynamic measurement of morphological and functional parameters in the mouse models of respiratory disease, with scan times as short as 30 s, based on the acquisition of projection images over six gantry rotations.
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 | 0.001 | 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".