Abstract
The overall aim of our project is to guide totally endoscopic coronary artery bypass. This requires construction of a 4D preoperative model of the coronary arteries and myocardium. The model must be aligned with the endoscopic view of the patient’s beating heart and presented to the surgeon using augmented reality. We propose that the model can be constructed from coronary CT. Segmentation can be performed for one phase of the cardiac cycle only and propagated to the others using non-rigid registration. We have compared the location of the coronaries produced by this method to hand segmentation.
Registration of the model to the endoscopic view of the patient is achieved in two phases. Temporal registration is performed by identification of corresponding motion between model and video. Then we calculate photo-consistency between the two da Vinci endoscope views and average over the frames of the motion model. This has been shown to improve the shape of the cost function. Phantom results are presented.
The model can then be transformed to the calibrated endoscope view and overlaid using two video mixers.
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Figl, M. et al. (2008). Coronary Motion Modelling for Augmented Reality Guidance of Endoscopic Coronary Artery Bypass. In: Bello, F., Edwards, P.J.E. (eds) Biomedical Simulation. ISBMS 2008. Lecture Notes in Computer Science, vol 5104. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70521-5_22
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DOI: https://doi.org/10.1007/978-3-540-70521-5_22
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