Markerless real-time 3-D target region tracking by motion backprojection from projection images

• Published in: IEEE transactions on medical imaging 2005-11, Vol.24 (11), p.1455-1468
• Main Authors: Rohlfing, T., Denzler, J., Grassl, C., Russakoff, D.B., Maurer, C.R.
• Format: Article
• Language: English
• Subjects: 2-D to 2-D registration; 2-D to 3-D registration; Algorithms; Artificial Intelligence; Computed tomography; Computer Systems; Costs; Frameless stereotactic radiosurgery; Humans; Image registration; Imaging, Three-Dimensional - methods; Medical treatment; motion backprojection; Motion estimation; Motion measurement; Movement; Mutual information; Neuronavigation - methods; Radiographic Image Enhancement - methods; Radiographic Image Interpretation, Computer-Assisted - methods; Radiosurgery - methods; real-time target tracking; Reproducibility of Results; Robustness; Sensitivity and Specificity; Subtraction Technique; Target tracking; X-ray imaging
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2005.857651

Accurate and fast localization of a predefined target region inside the patient is an important component of many image-guided therapy procedures. This problem is commonly solved by registration of intraoperative 2-D projection images to 3-D preoperative images. If the patient is not fixed during the intervention, the 2-D image acquisition is repeated several times during the procedure, and the registration problem can be cast instead as a 3-D tracking problem. To solve the 3-D problem, we propose in this paper to apply 2-D region tracking to first recover the components of the transformation that are in-plane to the projections. The 2-D motion estimates of all projections are backprojected into 3-D space, where they are then combined into a consistent estimate of the 3-D motion. We compare this method to intensity-based 2-D to 3-D registration and a combination of 2-D motion backprojection followed by a 2-D to 3-D registration stage. Using clinical data with a fiducial marker-based gold-standard transformation, we show that our method is capable of accurately tracking vertebral targets in 3-D from 2-D motion measured in X-ray projection images. Using a standard tracking algorithm (hyperplane tracking), tracking is achieved at video frame rates but fails relatively often (32% of all frames tracked with target registration error (TRE) better than 1.2 mm, 82% of all frames tracked with TRE better than 2.4 mm). With intensity-based 2-D to 2-D image registration using normalized mutual information (NMI) and pattern intensity (PI), accuracy and robustness are substantially improved. NMI tracked 82% of all frames in our data with TRE better than 1.2 mm and 96% of all frames with TRE better than 2.4 mm. This comes at the cost of a reduced frame rate, 1.7 s average processing time per frame and projection device. Results using PI were slightly more accurate, but required on average 5.4 s time per frame. These results are still substantially faster than 2-D to 3-D registration. We conclude that motion backprojection from 2-D motion tracking is an accurate and efficient method for tracking 3-D target motion, but tracking 2-D motion accurately and robustly remains a challenge.