A viscoelastic model of a breast phantom for real-time palpation
Bibliographic record
Abstract
Palpation of soft tissues helps to diagnose varying diseases within the tissues. Using a phantom, the current method of training palpation lacks for feedback of the training. Similar to a robot-assisted surgical system, a virtual reality (VR) system could be potential for such training due to its interactive nature. In such a VR system, studies revealed the observation that the human perception of objects is insensitive to subtle discrepancies in a simulation. Based upon this observation, we propose a real-time viscoelastic model of a breast phantom (as soft tissues). The model consists of a surface membrane and an inside gel. We evaluate this model through a comparison with a Finite Element Method (FEM) model, featuring physical parameters and different force contacts. The results show that the model can handle multi vertex force contact on an arbitrary location and yields reasonable accurate deformation compared to the FEM model.
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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".