Use of Temperature as a Contrast Agent in Electrical Impedance Tomography
Bibliographic record
Abstract
Electrical Impedance Tomography (EIT) images conductivity changes within a body from electrical measurements at the body surface. There is significant interest in using EIT to measure cardiovascular parameters, such as blood perfusion. Currently, a hypertonic bolus of saline is injected into a central vein, producing an increase in conductivity which is visualized. Unfortunately, hypertonic saline has undesirable effects in large doses, and cannot be used for continuous monitoring. We propose the use of temperature contrasting isotonic saline as a new contrast agent for EIT, suitable for repeated measurements. The experiments were carried out on a cylindrical tank filled with a saline solution having a conductivity of 1 S/m and the temperature of 22.6 ◦ C. A 280 ml saline bolus with the conductivity of 1 S/m and temperature difference ∆ t was injected at the tank center. We selected 5 different temperatures for the bolus. Subsequent EIT image analysis demon- strated that the temperature contrast can be successfully reconstructed. A quantitative analy- sis revealed that reconstructed impedance values were correlating linearly with temperature. Our initial results show the suitability of EIT for real- time noninvasive temperature contrast imaging.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".