Combinatorial optimization: algorithms and complexity
Combinatorial optimization: algorithms and complexity
C-arm tracking and reconstruction without an external tracker
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Optimal Matching for Prostate Brachytherapy Seed Localization with Dimension Reduction
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
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X-ray C-arm fluoroscopy is a natural choice for intraoperative seed localization in prostate brachy therapy. Resolving the correspondence of seeds in the projection images can be modeled as an assignment problem that is NP-hard. Our approach rests on the practical observation that the optimal solution has almost zero cost if the pose of the C-arm is known accurately. This allowed us to to derive an equivalent problem of reduced dimensionality that, with linear programming, can be solved efficiently in polynomial time. Additionally, our method demonstrates significantly increased robustness to C-arm pose errors when compared to the prior art. Because under actual clinical circumstances it is exceedingly difficult to track the C-arm, easing on this constraint has additional practical utility.