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A novel method of anatomical landmark selection for rib cage 3D reconstruction from biplanar radiography
- Source :
- Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. 8:15-23
- Publication Year :
- 2018
- Publisher :
- Informa UK Limited, 2018.
-
Abstract
- Methods to reconstruct anatomical structures in 3D are gaining interest in medicine because they give access to quantitative information on the patient’s geometry. However, these methods are user-dependent and require a trained operator, which is time consuming and a source of error and unreliability. The aim of this work was to validate a novel method of landmark selection to perform the 3D reconstruction of the rib cage from biplanar calibrated radiographies. The method uses digital painting for digitization of anatomical landmarks (eight ribs midlines, posterior extrema, sternum) to build a first estimate of the 3D ribcage geometry. Twenty scoliotic patients were included (Cobb angle: 43° ± 11°) and their ribcage was reconstructed twice with the proposed method by four trained operators. Measurement reproducibility was similar to previously validated methods. Uncertainty (95% CI) was 2.3° for the rib hump measurement, 9.7 mm and 3.8 mm for maximal antero-posterior and lateral diameter, 395 cm3 for ribcage volume. The method was qualitatively considered more user-friendly than previous versions, although it still requires a trained operator, and it took approximately 2 minutes of manual digitization. The new method should facilitate diffusion of 3D quantitative analysis of ribcage in clinical routine.
- Subjects :
- Computer science
3d analysis
Anatomical structures
Biomedical Engineering
Computational Mechanics
02 engineering and technology
Sciences de l'ingénieur
030218 nuclear medicine & medical imaging
03 medical and health sciences
0302 clinical medicine
0202 electrical engineering, electronic engineering, information engineering
Radiology, Nuclear Medicine and imaging
Computer vision
Selection (genetic algorithm)
Rib cage
business.industry
3D reconstruction
ingénierie bio-médicale [Sciences du vivant]
Biplanar radiography
Computer Science Applications
Anatomical landmark
Radiology Nuclear Medicine and imaging
020201 artificial intelligence & image processing
Artificial intelligence
business
Subjects
Details
- ISSN :
- 21681171 and 21681163
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
- Accession number :
- edsair.doi.dedup.....95afc70079b25b3a6bae19ffd6b54412