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Three-Dimensional Reconstruction of the Scoliotic Spine and Pelvis From Uncalibrated Biplanar x-Ray Images

2007· article· en· W1997677253 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Spinal Disorders & Techniques · 2007
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustinePolytechnique Montréal
Fundersnot available
KeywordsMedicinePelvis3D reconstructionScoliosisCalibrationArtificial intelligenceIterative reconstructionComputer visionRadiographyMedical physicsComputer scienceRadiologySurgeryMathematics

Abstract

fetched live from OpenAlex

Current three-dimensional (3D) reconstruction methods based on explicit or implicit calibration procedure require a calibration object to generate calibrated x-rays for the 3D reconstruction of the human spine and the pelvis. However, to conduct retrospective studies where no 3D technology is available, 3D reconstruction must be performed from x-ray images where no calibration object was used. The current state of the art offers a variety of methods to obtain a personalized 3D model of a patient's spine, however, none have presented a clinically proven method which allows a 3D reconstruction using uncalibrated x-rays. The main objective of this study was to propose a self-calibration method using only the anatomic content of the x-ray images and evaluate its clinical feasibility on uncalibrated x-ray images for the 3D reconstruction of the scoliotic spine and pelvis. The rationale for proposing a 3D reconstruction method from uncalibrated x-rays is to allow access to 3D evaluation of spinal deformities in any standard clinical setup and to enable the conduct of retrospective studies of any kind. To assess the validity of the 3D reconstructions yielded by the proposed algorithm, a clinical study using 60 pairs of digitized x-rays of children was conducted. The mean age for this group of 60 patients was of 14+/-3 (range 8 to 18) years old. All the children in the study group had scoliosis, with an average Cobb angle on the frontal plane of 25 degrees (range 3 to 70 degrees). For each case, a 3D reconstruction of the spine and pelvis was obtained using both explicit and self-calibration methods, from calibrated and uncalibrated x-rays, respectively. Results show that 3D reconstructions obtained with the proposed method from uncalibrated x-ray images yield- geometrical models that exhibit insignificant differences for 2D and 3D clinical indices commonly used in the evaluation of spinal deformities. This allows a 3D clinical assessment of scoliotic deformities from standard x-rays without the need for calibration, and providing access to this technology in any clinical setup and allowing to perform retrospective studies, which were previously impossible.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.011
GPT teacher head0.271
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it