Using lock-in infrared thermography for the visualization of the hand vascular tree
Bibliographic record
Abstract
An imaging technique of the hand vein tree is presented in this paper. Using the natural human circulatory system and a controlled armband pressure around the arm, a lock-in thermography technique with an internal excitation is carried out. Since the stimulation frequency is inversely proportional to the inspection depth, the subcutaneous layer requires the use of a very slow frequency. Thus, a sawtooth waveform is preferred to minimize the duration of the pressure applied to the armband during the experiment. A frequency of approximately 0.03 Hz and a pressure range between 100 and 140 mmHg, according to the diastolic and systolic blood pressure, are used as stimulation. Then, dorsal hand amplitude and phase images are obtained with IR_view (Klein, 1999), a tool specifically designed to analyze infrared images. The hand vein structure is thermally mapped by an infrared camera operating in the middle wavelength infrared range (MWIR) at room temperature. Parasitic frequencies are avoided by keeping the hand fixed. The resulting images show a gradient of temperature between surrounding tissues and the back-of-hand veins. The vascular signature segmentation is extracted from the amplitude and phase images by using a Fast Fourier Transform image processing technique. This work could be used for vein localization for perfusion or for the early diagnosis of vein diseases such as primitive varicose and deep vein thrombosis (DVT). A hand vein signature database for identification purposes is also possible.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".