EIT system and reconstruction algorithm adapted for skin cancer imaging
Bibliographic record
Abstract
To support early diagnosis of skin cancer and minimize the risk of developing metastases, electrical impedance tomography (EIT) is a promising technique. EIT is a bio-medical technique for imaging the electrical conductivity distribution of a body segment. The aim of this study is to adapt an EIT system for skin cancer screening. A 3-D finite element model (FEM) of the skin was first developed. This model was used to study the electrical behavior of cutaneous layers and identify the operating frequencies to properly discriminate malignant from benign lesions. Simulated data obtained with the FEM model were used to develop image reconstruction algorithms for visualizing and discriminating skin lesions. Furthermore, according to the specifications obtained from the model, electronic circuits and a handheld probe incorporating a disposable 16-electrode array were designed and built. The system and reconstruction algorithms were validated in vitro and measurements showed great correlation with simulations.
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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 | 0.000 | 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".