Efficient and cost‐effective 3D cellular imaging by sub‐voxel‐resolving light‐sheet add‐on microscopy
Bibliographic record
Abstract
Light-sheet fluorescence microscopy (LSFM) allows volumetric live imaging at high-speed and with low photo-toxicity. Various LSFM modalities are commercially available, but their size and cost limit their access by the research community. A new method, termed sub-voxel-resolving (SVR) light-sheet add-on microscopy (SLAM), is presented to enable fast, resolution-enhanced light-sheet fluorescence imaging from a conventional wide-field microscope. This method contains two components: a miniature add-on device to regular wide-field microscopes, which contains a horizontal laser light-sheet illumination path to confine fluorophore excitation at the vicinity of the focal plane for optical sectioning; an off-axis scanning strategy and a SVR algorithm that utilizes sub-voxel spatial shifts to reconstruct the image volume that results in a twofold increase in resolution. SLAM method has been applied to observe the muscle activity change of crawling C. elegans, the heartbeat of developing zebrafish embryo, and the neural anatomy of cleared mouse brains, at high spatiotemporal resolution. It provides an efficient and cost-effective solution to convert the vast number of in-service microscopes for fast 3D live imaging with voxel-super-resolved capability.
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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 | 0.000 |
| 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".