Semiautomatic classification of intervertebral disc degeneration in magnetic resonance images of the spine
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article describes the development of a quantitative method for computer-aided diagnosis (CAD) of intervertebral disc degeneration according to Pfirrmann's scale, a semiquantitative scale with five degrees of degeneration, in T2-weighted magnetic resonance images of the lumbar spine. The dataset consists of images of 210 discs obtained from 42 healthy individuals. The intervertebral discs were assigned Pfirrmann's grades based on independent and blind classification. Binary masks of manually segmented discs were used to compute the centroids of the regions, estimate the curvature of the spine by polynomial fitting, normalize intensities, and extract regions of interest. Texture analysis was performed using Haralick's features and moments were computed for each disc. Classification was performed using an artificial neural network using the full vectors of attributes as well as a reduced set obtained using gradient ascent search. An average true-positive rate of 75.2% and an average area under the receiver operating characteristic curve of 0.78 indicate potential application of this technique for CAD of spinal pathology.
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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 it