Automated tracking in digitized videofluoroscopy sequences for spine kinematic analysis

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摘要

Spine kinematic analysis provides useful information to aid understanding of the segmental motion of the vertebrae. Digitized videofluoroscopy (DVF) is the existing practical modality to image spine motion for kinematic data acquisition. However, obtaining kinematic parameters from DVF sequence requires manual landmarking which is a laborious process and can be subjective and error prone.This work develops an automated spine motion tracking algorithm for DVF sequences within a Bayesian framework. By utilizing the anatomical relationships between vertebrae, a dynamic Bayesian network with a particle filter at each node is constructed. The proposed algorithm overcomes the dimensionality problem in a regular particle filter and has more efficient and robust performance. It can provide results of about 1° and 2 pixels (0.2mm) variability in rotation and translation estimation, respectively, during repeated initialization analysis on sequences from simulation and in vivo healthy human subject studies.

论文关键词:Videofluoroscopy,Spine kinematics,Particle filter,Dynamic Bayesian network,Image processing

论文评审过程:Received 28 April 2008, Revised 7 December 2008, Accepted 15 February 2009, Available online 5 March 2009.

论文官网地址:https://doi.org/10.1016/j.imavis.2009.02.010