Computer-assisted and fractal-based morphometric assessment of microvascularity in histological specimens of gliomas
Bibliographic record
Abstract
Fractal analysis is widely applied to investigate the vascular system in physiological as well as pathological states. We propose and examine a computer-aided and fractal-based image analysis technique to quantify the microvascularity in histological specimens of WHO grade II and III gliomas. A computer-aided and fractal-based analysis was used to describe the microvessels and to quantify their geometrical complexity in histological specimens collected from 17 patients. The statistical analysis showed that the fractal-based indexes are the most discriminant parameters to describe the microvessels. The computer-aided quantitative analysis also showed that grade III gliomas are generally more vascularized than grade II gliomas. The fractal parameters are reliable quantitative indicators of the neoplastic microvasculature, making them potential surrogate biomarkers. The qualitative evaluation currently performed by the neuropathologist can be combined with the computer-assisted quantitative analysis of the microvascularity to improve the diagnosis and optimize the treatment of patients with brain cancer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".