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15 March 2019 2D pattern matching of frontal plane radiograph to 3D model identifies structural and functional deficiencies of spinal pelvic system in consideration of mechanical spine pain
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Abstract
Worldwide, back pain is the single leading cause of disability, preventing many people from engaging in work as well as other everyday activities. Back pain affects nearly 80% of the population at some point and is the most common cause for missed work (1). Most cases of back pain are mechanical or non-organic—meaning they are not caused by serious conditions, such as inflammatory arthritis, infection, fracture or cancer (2). However, there is no single procedure to identify the mechanical components related to spine pain. This study reports on the development and application of a computer aided drafting (CAD) program that identifies structural and functional deficits of the spinal pelvic system from two dimensional radiographs. When injury to the spinal system disturbs balance or visual orientation, the righting reflex activates a compensatory response using muscle contraction and mass displacement. This mechanical displacement process proceeds along the pathway of the coupled motions of gait including pelvic and spine rotation. The gait cycle is the motion pathway of the body and the gait cycle is the primary pathway of mechanical compensation. As a result of injury, the spine adapts into a compensatory non-neutral position of gait with all its associated coupled motions. This compensatory, non-neutral position of gait becomes inherent to the spinal system and is recorded on a patient’s weight bearing x-rays. Therefore, a static biomechanical model of the spine and pelvis in a non-neutral position of gait is needed for patient comparison to assess structural integrity including mechanical and functional efficiency.
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Raymond Wiegand "2D pattern matching of frontal plane radiograph to 3D model identifies structural and functional deficiencies of spinal pelvic system in consideration of mechanical spine pain", Proc. SPIE 10953, Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, 109531U (15 March 2019); https://doi.org/10.1117/12.2512247
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