Sketch-based volumetric seeded region growing
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
Interactive volume segmentation is an essential and important step in medical image processing. Conventional interactive methods typically demand significant amounts of time and do not lend to a natural interaction scheme with the 3D volume. In this paper we present a sketch-based interface for seeded region growing volume segmentation. In our approach, the user freely sketches regions of interest (ROI) directly over the 3D volume. Parts of the volume outside the ROIs are then automatically cut out in real-time. The user repeats this process as many times as necessary until he/she decides to specify the seed point 3D location directly at the ROI. To prevent unexpected segmentations, the region growing is restricted to the specified ROI. Our sketch-based system utilizes GPU programming to achieve real-time processing for both rendering and volumetric cutting independent from the size and shape of the sketched strokes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it