Low-cost three-dimensional imaging system combining fluorescence and ultrasound
Bibliographic record
Abstract
In this paper, we present a dual-modality imaging system combining three-dimensional (3D) continuous-wave transillumination fluorescence tomography with 3D ultrasound (US) imaging. We validated the system with two phantoms, one containing fluorescent inclusions (Cy5.5) at different depths, and another varying-thickness semicylindrical phantom. Using raster scanning, the combined fluorescence/US system was used to collect the boundary fluorescent emission in the X-Y plane, as well as recovered the 3D surface and position of the inclusions from US signals. US images were segmented to provide soft priors for the fluorescence image reconstruction. Phantom results demonstrated that with priors derived from the US images, the fluorescent reconstruction quality was significantly improved. As further evaluation, we show pilot in vivo results using an Apo-E mouse to assess the feasibility and performance of this system in animal studies. Limitations and potential to be used in artherosclerosis studies are then discussed.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".