Abstract
3D modelling can be used for a variety of purposes, including biomedical modelling for orthopaedic or anatomical applications. Low back pain is prevalent in society yet few validated 3D models of the lumbar spine exist to facilitate assessment. We therefore created a 3D surface data set for lumbar vertebrae from human vertebrae. Models from 86 lumbar vertebrae were constructed using an inexpensive method involving image capture by digital camera and reconstruction of 3D models via an image-based technique. The reconstruction method was validated using a laser-based arm scanner and measurements derived from real vertebrae using electronic callipers. Results show a mean relative error of 5.2% between image-based models and real vertebrae, a mean relative error of 4.7% between image-based and arm scanning models and 95% of vertices’ errors are less than 3.5 millimetres with a median of 1.1 millimetres. The accuracy of the method indicates that the generated models could be useful for biomechanical modelling or 3D visualisation of the spine.
Highlights
1 http://www.turbosquid.com/3d-model/anatomy/spine 2 http://www.3dcadbrowser.com/3dmodels.aspx?collection=anatomy 3 http://spineweb.digitalimaginggroup.ca/Art. 9, page 2 of 15Bennani et al: Three Dimensional (3D) Lumbar Vertebrae Data SetAcquiring 3D images from active scanners such as laser, structured light scanners or sonar scanners has limitations
These scanners send a signal into the environment and measure the effect the environment has on the signal; they can produce very accurate 3D reconstructions but they can be expensive depending on the accuracy required
This study has examined an inexpensive method of providing a 3D reconstruction of a complex anatomical shape
Summary
Bennani et al: Three Dimensional (3D) Lumbar Vertebrae Data Set. Acquiring 3D images from active scanners such as laser, structured light scanners or sonar scanners has limitations. Acquiring 3D images from active scanners such as laser, structured light scanners or sonar scanners has limitations These scanners send a signal into the environment and measure the effect the environment has on the signal; they can produce very accurate 3D reconstructions but they can be expensive depending on the accuracy required. The only equipment required is a digital camera, a computer, and the relevant software. This option is very inexpensive, very flexible and easy to use. If camera positions and geometry are unknown, they too must be estimated, but this is possible and common for such data (Seitz, et al, 2006)
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