Non-invasive in-vivo 3-D imaging of small animals using spatially filtered enhanced truncated-correlation photothermal coherence tomography
Bibliographic record
Abstract
We present enhanced truncated-correlation phototothermal coherence tomography (eTC-PCT) for non-invasive three-dimensional imaging of small animals. Tumor detection is reported in a mouse thigh by injecting cancerous cells in the thigh followed by eTC-PCT imaging. Detection of the tumor 3 days after injection may lead to potential for using the eTC-PCT method for cancer treatment studies. eTC-PCT was also applied successfully to non-invasive in-vivo mouse brain structural imaging. A unique spatial-gradient-gate adaptive filter was introduced in a scanned mode along the (x,y) coordinates of camera images from different sub-cranial depths, revealing absorber true spatial extent from diffusive photothermal images and restoring pre-diffusion lateral image resolution beyond the Rayleigh criterion limit in diffusion-wave imaging science. The spatial resolution and contrast enhancement demonstrated in photothermal in-vivo and ex-vivo images of the mouse brain revealed not only vascular structures but also other brain structures, such as the brain hemispheres, cerebellum, and olfactory lobes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".