3D morphological measurement of whole slide histological vasculature reconstructions
Bibliographic record
Abstract
Properties of the microvasculature that contribute to tissue perfusion can be assessed using immunohistochemistry on 2D histology sections. However, the vasculature is inherently 3D and the ability to measure and visualize the vessel wall components in 3D will aid in detecting focal pathologies. Our objectives were (1) to develop a method for 3D measurement and visualization of microvasculature in 3D, (2) to compare the normal and regenerated post-ischemia mouse hind limb microvasculature, and (3) to compare the 2D and 3D vessel morphology measures. Vessels were stained for smooth muscle using 3,3'-Diaminobenzidine (DAB) immunostain for both normal (n = 6 mice) and regenerated vasculature (n = 5 mice). 2D vessel segmentations were reconstructed into 3D using landmark based registration. No substantial bias was found in the 2D measurements relative to 3D, but larger differences were observed for individual vessels oriented non-orthogonally to the plane of sectioning. A larger value of area, perimeter, and vessel wall thickness was found in the normal vasculature as compared to the regenerated vasculature, for both the 2D and 3D measurements (<i>p</i> < 0.01). Aggregated 2D measurements are sufficient for identifying morphological differences between groups of mice; however, one must interpret individual 2D measurements with caution if the vessel centerline direction is unknown. Visualization of 3D measurements permits the detection of localized vessel morphology aberrations that are not revealed by 2D measurements. With vascular measure visualization methodologies in 3D, we are now capable of locating focal pathologies on a whole slide level.
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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 | 0.000 |
| 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".