Fast reconstruction of volumetric models of anatomical structures
Bibliographic record
Abstract
This paper reports a fast and robust method for building 3D volumetric models of anatomical structures. The proposed reconstruction solution is image modality independent. As input, the method requires a set of contours obtained after organ segmentation. It is not necessary for contours to lie on parallel slices. The contours are simplified using a combination of smoothing techniques and B-splines. A 3D triangulation of the object convex hull is generated, based on a 3D Delaunay triangulation algorithm. A sculpting process of the non-object tetrahedra is performed, based on the spatial information obtained in the segmentation process. The surface, represented as a set of triangles, and the volume, represented as a set of tetrahedral, are obtained. To validate the algorithm, geometrical measurements of the generated model are computed, and compared with the original object. Currently, the method is tested on CT and MR images. At this stage, 2 seconds are needed on a standard workstation to build a skull model with approximately 120,000 tetrahedrals.
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.
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 | 0.001 |
| 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) | 0.000 | 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".