Intensity Integrated Laplacian-Based Thickness Measurement for Detecting Human Metaphase Chromosome Centromere Location
Bibliographic record
Abstract
Accurate detection of the human metaphase chromosome centromere is an important step in many chromosome analysis and medical diagnosis algorithms. The centromere location can be utilized to derive information such as the chromosome type, polarity assignment, etc. Methods available in the literature yield unreliable results mainly due to high variability of morphology in metaphase chromosomes and boundary noise present in the image. In this paper, we have proposed a multistaged algorithm which includes the use of discrete curve evolution, gradient vector flow active contours, functional approximation of curve segments, and support vector machine classification. The standard Laplacian thickness measurement algorithm was enhanced to incorporate both contour information as well as intensity information to obtain a more accurate centromere location. In addition to segmentation and width profile measurement, the proposed algorithm can also correct for sister chromatid separation in cell images. The proposed method was observed to be more accurate and statistically significant as compared to a centerline-based method when tested with 226 human metaphase chromosomes.
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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".