A systematic approach to feature tracking of lumbar spine vertebrae from fluoroscopic images using complex-valued wavelets.
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.
Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada. a28wong@engmail.uwaterloo.ca
Alexander
A
Wong
Nadine M
NM
Dunk
Jack P
JP
Callaghan
D000465:Algorithms; D005471:Fluoroscopy; D006801:Humans; D008159:Lumbar Vertebrae / Q000033:anatomy & histology*