Part-Based Lumbar Vertebrae Tracking in Videofluoroscopy Using Particle Filter
Vertebrae tracking in videofluoroscopy is a challenging problem because of the low quality of image sequences, like poor image contrast, ambiguous geometry details, and vertebrae rotation. The aim of this article is to tackle this problem by proposing a method for rigid object tracking based on the fragmentation of the tracked object. The proposed method is based on the particle filter using the calculation of the similarity between the respective fragments of objects instead of the whole objects. The similarity measures used are the Jaccard index, the correlation coefficient, and the Bhattacharyya coefficient. The tracking starts with a semi-automatic initialization. The results show that the fragments-based object tracking method outperforms the classical method (without fragmentation) for each of the used similarity measures. The results show that the tracking based on the Jaccard index is more stable and outperforms methods based on other similarity measures.