Development of a PET Scanner for Simultaneously Imaging Small Animals with MRI and PET
Bibliographic record
Abstract
Recently, positron emission tomography (PET) is playing an increasingly important role in the diagnosis and staging of cancer. Combined PET and X-ray computed tomography (PET-CT) scanners are now the modality of choice in cancer treatment planning. More recently, the combination of PET and magnetic resonance imaging (MRI) is being explored in many sites. Combining PET and MRI has presented many challenges since the photo-multiplier tubes (PMT) in PET do not function in high magnetic fields, and conventional PET detectors distort MRI images. Solid state light sensors like avalanche photo-diodes (APDs) and more recently silicon photo-multipliers (SiPMs) are much less sensitive to magnetic fields thus easing the compatibility issues. This paper presents the results of a group of Canadian scientists who are developing a PET detector ring which fits inside a high field small animal MRI scanner with the goal of providing simultaneous PET and MRI images of small rodents used in pre-clinical medical research. We discuss the evolution of both the crystal blocks (which detect annihilation photons from positron decay) and the SiPM array performance in the last four years which together combine to deliver significant system performance in terms of speed, energy and timing resolution.
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 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".