PURPOSE: This paper analyses the effects of error sources which can be found in patient alignment systems. As an example, an ultrasound (US) repositioning system and its transformation chain are assessed. The findings of this concept can also be applied to any navigation system. METHODS AND MATERIALS: In a first step, all error sources were identified and where applicable, corresponding target registration errors were computed. By applying error propagation calculations on these commonly used registration/calibration and tracking errors, we were able to analyse the components of the overall error. Furthermore, we defined a special situation where the whole registration chain reduces to the error caused by the tracking system. Additionally, we used a phantom to evaluate the errors arising from the image-to-image registration procedure, depending on the image metric used. We have also discussed how this analysis can be applied to other positioning systems such as Cone Beam CT-based systems or Brainlab's ExacTrac. RESULTS: The estimates found by our error propagation analysis are in good agreement with the numbers found in the phantom study but significantly smaller than results from patient evaluations. We probably underestimated human influences such as the US scan head positioning by the operator and tissue deformation. Rotational errors of the tracking system can multiply these errors, depending on the relative position of tracker and probe. CONCLUSIONS: We were able to analyse the components of the overall error of a typical patient positioning system. We consider this to be a contribution to the optimization of the positioning accuracy for computer guidance systems.
PURPOSE: This paper analyses the effects of error sources which can be found in patient alignment systems. As an example, an ultrasound (US) repositioning system and its transformation chain are assessed. The findings of this concept can also be applied to any navigation system. METHODS AND MATERIALS: In a first step, all error sources were identified and where applicable, corresponding target registration errors were computed. By applying error propagation calculations on these commonly used registration/calibration and tracking errors, we were able to analyse the components of the overall error. Furthermore, we defined a special situation where the whole registration chain reduces to the error caused by the tracking system. Additionally, we used a phantom to evaluate the errors arising from the image-to-image registration procedure, depending on the image metric used. We have also discussed how this analysis can be applied to other positioning systems such as Cone Beam CT-based systems or Brainlab's ExacTrac. RESULTS: The estimates found by our error propagation analysis are in good agreement with the numbers found in the phantom study but significantly smaller than results from patient evaluations. We probably underestimated human influences such as the US scan head positioning by the operator and tissue deformation. Rotational errors of the tracking system can multiply these errors, depending on the relative position of tracker and probe. CONCLUSIONS: We were able to analyse the components of the overall error of a typical patient positioning system. We consider this to be a contribution to the optimization of the positioning accuracy for computer guidance systems.
Authors: Michael Pinkawa; Martin Pursch-Lee; Branka Asadpour; Bernd Gagel; Marc D Piroth; Jens Klotz; Sandra Nussen; Michael J Eble Journal: Strahlenther Onkol Date: 2008-12-24 Impact factor: 3.621
Authors: S A Pawiro; P Markelj; F Pernus; C Gendrin; M Figl; C Weber; F Kainberger; I Nöbauer-Huhmann; H Bergmeister; M Stock; D Georg; H Bergmann; W Birkfellner Journal: Med Phys Date: 2011-03 Impact factor: 4.071