@article {282,
	title = {A systematic approach to feature tracking of lumbar spine vertebrae from fluoroscopic images using complex-valued wavelets},
	journal = {Computer Methods in Biomechanics and Biomedical Engineering},
	volume = {12},
	year = {2009},
	abstract = {<p>This paper presents a systematic approach to lumbar spine vertebrae tracking in fluoroscopic images using complex-valued wavelets. The proposed algorithm is designed specifically based on a set of performance criteria associated with the detection and tracking of feature points in lumbar spine vertebrae from fluoroscopic images. The algorithm handles contrast and illumination non-homogeneities and noise in fluoroscopic images through the use of local phase information obtained using complex-valued wavelets. The algorithm is capable of tracking feature points that undergo various geometric deformations caused during the fluoroscopic imaging process by defining a descriptor that is invariant to scale and rotation and robust to affine, projective and mild pin-cushion distortions. The algorithm has been tested using dynamic sagittal fluoroscopic videos of the lumbar-sacral region and testing results indicate that the algorithm achieves good tracking performance of lumbar spine vertebrae in fluoroscopic images that exhibit contrast and illumination non-homogeneities as well as noise, with mean root mean square error of less than 0.40 mm under in all test sequences.</p>
},
	keywords = {complex-valued wavelets, fluoroscopic images, lumbar spine, tracking, vertebrae},
	doi = {http://dx.doi.org/10.1080/10255840902802891},
	url = {http://www.tandfonline.com/doi/abs/10.1080/10255840902802891},
	author = {A Wong and N M. Dunk and J Callaghan}
}
