New Image Similarity Measure for Bronchoscope Tracking Based on Image Registration
This paper presents new image similarity measure for bronchoscope tracking based on image registration between real and virtual endoscopic images. A function for bronchoscope tracking is one of the fundamental functions in a bronchoscope navigation system. Since it is difficult to attach a positional sensor at the tip of the bronchoscope due to the space limitation, image registration between real endoscopic (RE) and virtual endoscopic (VE) images becomes a strong tool for bronchoscopic camera motion tracking. The summing-type image similarity measuring methods including mean squared error or mutual information could not properly estimate the position and orientation of the endoscope, since the outputs of these methods do not change significantly due to averaging. This paper proposes new image similarity measure that effectively uses characteristic structures observed in bronchoscopic views in similarity computation. This method divides the original image into a set of small subblocks and selects only the subblocks in which characteristic shapes are seen. Then, an image similarity value is calculated only inside the selected subblocks. We applied the proposed method to eight pairs of X-ray CT images and real bronchoscopic videos. The experimental showed much improvement in continuous tracking performance. Nearly 1000 consecutive frames were tracked correctly.
- 1.Rogalla, P., Terwisscha van Scheltinga, J., Hamm, B. (eds.): Virtual endoscopy and related 3D techniques. Springer, Berlin (2001)Google Scholar
- 4.Helferty, J.P., Higgins, W.E.: Technique for Registering 3D Virtual CT Images to Endoscopic Video. In: Proceedings of ICIP (International Conference on Image Processing), pp. 893–896 (2001)Google Scholar
- 5.Mori, K., Suenaga, Y., Toriwaki, J.: Fast volume rendering based on software optimization using multimedia instructions on PC platform. In: Proceedings of Computer Assisted Radiology and Surgery (CARS)2002, pp. 467–472 (2002)Google Scholar