A prototype hand-held tri-modal instrument for <i>in vivo</i> ultrasound, photoacoustic, and fluorescence imaging
Bibliographic record
Abstract
Multi-modality imaging is beneficial for both preclinical and clinical applications as it enables complementary information from each modality to be obtained in a single procedure. In this paper, we report the design, fabrication, and testing of a novel tri-modal in vivo imaging system to exploit molecular/functional information from fluorescence (FL) and photoacoustic (PA) imaging as well as anatomical information from ultrasound (US) imaging. The same ultrasound transducer was used for both US and PA imaging, bringing the pulsed laser light into a compact probe by fiberoptic bundles. The FL subsystem is independent of the acoustic components but the front end that delivers and collects the light is physically integrated into the same probe. The tri-modal imaging system was implemented to provide each modality image in real time as well as co-registration of the images. The performance of the system was evaluated through phantom and in vivo animal experiments. The results demonstrate that combining the modalities does not significantly compromise the performance of each of the separate US, PA, and FL imaging techniques, while enabling multi-modality registration. The potential applications of this novel approach to multi-modality imaging range from preclinical research to clinical diagnosis, especially in detection/localization and surgical guidance of accessible solid tumors.
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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 | 0.000 |
| 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".