Application of HDMI<sup>®</sup> cables as an MRI compatible single cable solution for Readout and power supply of SiPM based PET detectors
Bibliographic record
Abstract
All PET detectors require cabling to supply power and transmit data, whether in analog or digital form. In this work we examine using High-Definition Multimedia Interface (HDMI®) cables as a single cable solution to both supply power and transmit analog signals for a SiPM based PET detector that will be used in a hybrid PET/MRI imaging system. HDMI cables are designed for digital audio/video transmission, with each cable having four pairs of shielded 100 ohm differential signal lines, each rated for 3.4 Gbit/s, along with 7 additional signal lines and a braided shield around the entire cable. While designed as a digital signal cable, the lines are rated for 40V DC and 0.5A current. To test using HDMI® cables for application in PET, a silicon photomultiplier (SiPM) PET detector module with a single HDMI® Type C ('mini) receptacle was built using a SensL SPMArray4 coupled to a dual-layer offset LYSO crystal array 1.67 mm crystal pitch. The 16 detector outputs were multiplexed to four signals using a simple resistor charge division network and driven using Analog Devices AD8132 op-amps. Detector bias of 30.2V and +/-5V power for the op-amps was supplied through a 25' length HDMI® cable connected through a custom receiver card. The signals were processed using NIM electronics and digitized with a PC based analog to digital converter (ADC) card. The PET detector had an average energy resolution of 14.3% full-width at half-maximum (FWHM) and an average timing resolution of 2.50 ns. The performance of the PET detector was unaffected when operated inside a 7T MRI system. The MR images showed degradation in signal to noise ratio (SNR) of between 7 and 23%, which is believe to be due to coupling between the RF coil and the PET detector shielding. The results of this work suggest that HDMI® cab
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".