WE‐C‐WAB‐05: A Novel Integrated X‐Ray and Fluorescence Tomography System for Small Animal Radiation Research Platform
Bibliographic record
Abstract
Purpose: A novel, low cost, and fast acquisition fluorescence tomography (FT) system was designed and built for preclinical focal radiation research to provide soft tissue guidance as well as to support highly sensitive functional imaging. Materials & Methods: The cone beam (CB) CT/FT system was designed and tested in a standalone form. The mouse is placed prone on a rotation stage. The x‐ray source and flat panel detector for the CBCT are aligned perpendicular to the mouse anterior‐posterior axis. The anatomical information obtained from CBCT is used as prior information to enhance subsequent optical reconstruction by limiting the solution space. Prior to FT acquisition, diffuse optical tomography (DOT) is performed to reconstruct the animal optical properties. Optical fibers at fixed positions in contact with the animal deliver the source light of different wavelengths for DOT. For FT, a diode laser replaces the lamp as the excitation source. A CCD camera with f/1.4 lens is used as the optical detector. The CCD camera response readout was calibrated using an integrating sphere to provide the absolute light fluence rate at the desired wavelength. A mirror system capable of 90 degree rotation around the animal reflects the optical signal to the CCD camera. Results: To test the FT system, pre‐drilled holes in a tissue‐simulating phantom were filled with a solution of indocyanine green (ICG). Several scenarios were used to test the optical system, such as examining the spatial resolution by placing the same fluorophore at variable separations, and reconstructing the ICG and another infrared fluorophore simultaneously to simulate multiple color functional imaging. Our initial results show that FT can localize the ICG source to within 1 mm. Conclusion: The novel CBCT/FT system presents new research opportunities for image guided pre‐clinical radiation research.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".