Quantitative error analysis for computer assisted navigation: A feasibility study
Purpose: The benefit of computer-assisted navigation depends on the registration process, at which patient features are correlated to some preoperative imagery. The operator-induced uncertainty in localizing patient features—the user localization error (ULE)—is unknown and most likely dominating the...
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Veröffentlicht in: | Medical physics (Lancaster) 2013-02, Vol.40 (2), p.021910-n/a |
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Sprache: | eng |
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Zusammenfassung: | Purpose:
The benefit of computer-assisted navigation depends on the registration process, at which patient features are correlated to some preoperative imagery. The operator-induced uncertainty in localizing patient features—the user localization error (ULE)—is unknown and most likely dominating the application accuracy. This initial feasibility study aims at providing first data for ULE with a research navigation system.
Methods:
Active optical navigation was done in CT-images of a plastic skull, an anatomic specimen (both with implanted fiducials), and a volunteer with anatomical landmarks exclusively. Each object was registered ten times with 3, 5, 7, and 9 registration points. Measurements were taken at 10 (anatomic specimen and volunteer) and 11 targets (plastic skull). The active NDI Polaris system was used under ideal working conditions (tracking accuracy 0.23 mm root-mean-square, RMS; probe tip calibration was 0.18 mm RMS). Variances of tracking along the principal directions were measured as 0.18 mm2, 0.32 mm2, and 0.42 mm2. ULE was calculated from predicted application accuracy with isotropic and anisotropic models and from experimental variances, respectively.
Results:
The ULE was determined from the variances as 0.45 mm (plastic skull), 0.60 mm (anatomic specimen), and 4.96 mm (volunteer). The predicted application accuracy did not yield consistent values for the ULE.
Conclusions:
Quantitative data of application accuracy could be tested against prediction models with iso- and anisotropic noise models and revealed some discrepancies. This could potentially be due to the facts that navigation and one prediction model wrongly assume isotropic noise (tracking is anisotropic), while the anisotropic noise prediction model assumes an anisotropic registration strategy (registration is isotropic in typical navigation systems). The ULE data are presumably the first quantitative values for the precision of localizing anatomical landmarks and implanted fiducials. Submillimetric localization is possible for implanted screws; anatomic landmarks are not suitable for high-precision clinical navigation. |
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ISSN: | 0094-2405 2473-4209 |
DOI: | 10.1118/1.4773871 |