title: Motion-adapted catheter navigation with real-time instantiation and improved visualisation.
abstract: The improvements to catheter manipulation by the use of robot-assisted catheter navigation for endovascular procedures include increased precision, stability of motion and operator comfort. However, navigation through the vasculature under fluoroscopic guidance is still challenging, mostly due to physiological motion and when tortuous vessels are involved. In this paper, we propose a motion-adaptive catheter navigation scheme based on shape modelling to compensate for these dynamic effects, permitting predictive and dynamic navigations. This allows for timed manipulations synchronised with the vascular motion. The technical contribution of the paper includes the following two aspects. Firstly, a dynamic shape modelling and real-time instantiation scheme based on sparse data obtained intra-operatively is proposed for improved visualisation of the 3D vasculature during endovascular intervention. Secondly, a reconstructed frontal view from the catheter tip using the derived dynamic model is used as an interventional aid to user guidance. To demonstrate the practical value of the proposed framework, a simulated aortic branch cannulation procedure is used with detailed user validation to demonstrate the improvement in navigation quality and efficiency.
authors.affiliation: Hamlyn Centre for Robotic Surgery, Imperial College London, London SW7 2AZ, UK. su-lin.lee@imperial.ac.uk.
authors.forename: Su-Lin
authors.initials: SL
authors.lastname: Lee
authors.affiliation: Hamlyn Centre for Robotic Surgery, Imperial College London, London SW7 2AZ, UK.
authors.forename: Ka-Wai
authors.initials: KW
authors.lastname: Kwok
authors.affiliation: Hamlyn Centre for Robotic Surgery, Imperial College London, London SW7 2AZ, UK.
authors.forename: Lichao
authors.initials: L
authors.lastname: Wang
authors.affiliation: Hamlyn Centre for Robotic Surgery, Imperial College London, London SW7 2AZ, UK.
authors.forename: Celia
authors.initials: C
authors.lastname: Riga
authors.affiliation: Academic Division of Surgery, Imperial College London, London, UK.
authors.forename: Colin
authors.initials: C
authors.lastname: Bicknell
authors.affiliation: Academic Division of Surgery, Imperial College London, London, UK.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Cheshire
authors.affiliation: Hamlyn Centre for Robotic Surgery, Imperial College London, London SW7 2AZ, UK.
authors.forename: Guang-Zhong
authors.initials: GZ
authors.lastname: Yang
keywords: Endovascular intervention; Image-guided intervention; Minimally invasive surgery; Motion prediction; Robotic surgery; Shape modelling
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