Abstract
Purpose
With the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures.
Methods
We developed two feature detection methods (2D and pseudo-3D) based on SURF key points and also transferred the SURF approach to 3D. Combined with an atlas-based registration, our algorithm adjusts the standard planes of the calcaneal C-arm images automatically. The robustness of the algorithms is evaluated using a clinical data set. Additionally, we tested the algorithm’s performance for two registration approaches, two resolutions of C-arm images and two methods for metal artifact reduction.
Results
For the feature extraction, the novel 3D-SURF approach performs best. As expected, a higher resolution (\(512^3\) voxel) leads also to more robust feature points and is therefore slightly better than the \(256^3\) voxel images (standard setting of device). Our comparison of two different artifact reduction methods and the complete removal of metal in the images shows that our approach is highly robust against artifacts and the number and position of metal implants.
Conclusions
By introducing our fast algorithmic processing pipeline, we developed the first steps for a fully automatic assistance system for the assessment of C-arm CT images.
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Michael Brehler, Joseph Görres, Jochen Franke, Karl Barth, Sven Y. Vetter, Paul A. Grützner, Hans-Peter Meinzer, Ivo Wolf and Diana Nabers declare that they have no conflict of interest.
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This work was partially funded by Siemens Healthcare, X-ray Products.
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Brehler, M., Görres, J., Franke, J. et al. Intra-operative adjustment of standard planes in C-arm CT image data. Int J CARS 11, 495–504 (2016). https://doi.org/10.1007/s11548-015-1281-3
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DOI: https://doi.org/10.1007/s11548-015-1281-3