Article ID Journal Published Year Pages File Type
6951078 Biomedical Signal Processing and Control 2017 8 Pages PDF
Abstract
Three dimensional reconstruction is essential in accurate diagnosis of numerous spinal deformities which are 3D in nature. The stereo-radiographic reconstruction involving bi-planar X-rays is one of the most commonly used methods. Algorithms with stereo-corresponding point (SCP) or non-stereo-corresponding point (NSCP) can be used to achieve this 3D reconstruction. But, the NSCP method is slower and needs manual identification of many anatomical landmarks. Hence it suffers from observer variability and has restricted usage in normal clinical setup. Thus, a hybrid method is proposed in which the SCP reconstructed model is refined using the geometric features from the X-rays to achieve the accuracy closest to NSCP method. The SCP model is constructed using the X-rays on a calibration bench from the scoliotic subject. From these X-rays the vertebral features are extracted automatically. The SCP model structure is refined using the geometric transformations according to the extracted features. The 3D model thus formed is called combined SCP and geometric (CSCPG) reconstruction. By considering the NSCP model as a reference, both qualitative and quantitative approaches are followed to validate the proposed model. The CSCPG method has lesser observer variability as it needs only six anatomical landmarks per vertebra. Further, it is faster and the reconstruction error is within the acceptable limits. To quantify the deformities like axial vertebral rotation and spinal curvature novel methods have been proposed. The axial vertebral rotation is measured using simple vertebra vector parametric computations. It needs identification of only two landmarks per vertebra for angle measurement. The apical vertebra gives the plane of maximum curvature. The actual spinal curvature has to be computed on this plane. A semi-automatic method is proposed to compute this curvature using a new projection technique. The deformity quantification methods are validated using manual measurements as well as the results from standard approaches. Hence, a fast, simple and economic 3D diagnostic method is developed for quantification of the spinal deformities.
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Physical Sciences and Engineering Computer Science Signal Processing
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