Evaluation of a Robust Fiducial Tracking Algorithm for Image-guided Radiosurgery

摘要

Fiducial tracking is a widely used method in image guided procedures such as image guided radiosurgery and radiotherapy. Our group has developed a new fiducial identification algorithm, concurrent Viterbi with association (CVA) algorithm, based on a modified Hidden Markov Model (HMM), and reported our initial results previously. In this paper, we present an extensive performance evaluation of this novel algorithm using phantom testing and clinical images acquired during patient treatment. For a common three-fiducial case, the algorithm execution time is less than two seconds. Testing with a collection of images from more than 35 patient treatments, with a total of more than 10000 image pairs, we find that the success rate of the new algorithm is better than 99%. In the tracking test using a phantom, the phantom is moved to a variety of positions with translations up to 8 mm and rotations up to 4 degree. The new algorithm correctly tracks the phantom motion, with an average translation error of less than 0.5 mm and rotation error less than 0.5 degrees. These results demonstrate that the new algorithm is very efficient, robust, easy to use, and capable of tracking fiducials in a large region of interest (ROI) at a very high success rate with high accuracy.