Motion-tolerant 3D volumetric multimodality microscopy imaging of human skin with subcellular resolution and extended field-of-view
Bibliographic record
Abstract
The skin, the body's largest organ, has a heterogeneous structure with various cell types and tissue layers. In vivo noninvasive 3D volumetric imaging with multi-contrast, high resolution, a large field-of-view (FOV), and no-motion artifacts is crucial for studying skin biology and diagnosing/evaluating diseases. Traditionally high-resolution in vivo skin microscopy methods capture images in the en-face (xy) plane parallel to the skin surface but are affected by involuntary motion, particularly during large-area volumetric data acquisition using xy-z mosaicking. In this work, we developed an xz-y imaging method that acquires images in the vertical (xz) plane and extends the FOV by moving the skin laterally along the y-direction. This approach is conceived based on our observation that involuntary skin movements are mostly along the vertical direction. Combined with a unique motion correction method, it enables 3D image reconstruction with subcellular resolution and an extended FOV close to a centimeter (8 mm). A multimodality microscopy system using this method provides simultaneous reflectance confocal, two-photon excited fluorescence, and second harmonic generation imaging, enabling multi-contrast capabilities. Using this system, we captured histology-like features of normal skin, vitiligo, and melanoma, demonstrating its potential for in vivo skin biology studies, clinical diagnosis, treatment planning and monitoring.
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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 | 0.001 |
| 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".