Abstract
We present a needle deflection estimation method to compensate for needle bending during insertion into deformable tissue. We combine a kinematic needle deflection estimation model, electromagnetic (EM) trackers, and a Kalman filter (KF). We reduce the impact of error from the needle deflection estimation model by using the fusion of two EM trackers to report the approximate needle tip position in real-time. One reliable EM tracker is installed on the needle base, and estimates the needle tip position using the kinematic needle deflection model. A smaller but much less reliable EM tracker is installed on the needle tip, and estimates the needle tip position through direct noisy measurements. Using a KF, the sensory information from both EM trackers is fused to provide a reliable estimate of the needle tip position with much reduced variance in the estimation error. We then implement this method to compensate for needle deflection during simulated prostate cancer brachytherapy needle insertion. At a typical maximum insertion depth of 15 cm, needle tip mean estimation error was reduced from 2.39 mm to 0.31 mm, which demonstrates the effectiveness of our method, offering a clinically practical solution.
Original language | English (US) |
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Title of host publication | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
Pages | 952-955 |
Number of pages | 4 |
DOIs | |
State | Published - 2012 |
Externally published | Yes |
Event | 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States Duration: Aug 28 2012 → Sep 1 2012 |
Other
Other | 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 |
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Country/Territory | United States |
City | San Diego, CA |
Period | 8/28/12 → 9/1/12 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Biomedical Engineering
- Health Informatics