Real-time geometry-aware augmented reality in minimally invasive surgery
Authors: Chen, L., Tang, W. and John, N.W.
Journal: Healthcare Technology Letters
Volume: 4
Issue: 5
Pages: 163-167
eISSN: 2053-3713
DOI: 10.1049/htl.2017.0068
Abstract:The potential of augmented reality (AR) technology to assist minimally invasive surgery (MIS) lies in its computational performance and accuracy in dealing with challenging MIS scenes. Even with the latest hardware and software technologies, achieving both real-time and accurate augmented information overlay in MIS is still a formidable task. In this Letter, the authors present a novel real-time AR framework for MIS that achieves interactive geometric aware AR in endoscopic surgery with stereo views. The authors' framework tracks the movement of the endoscopic camera and simultaneously reconstructs a dense geometric mesh of the MIS scene. The movement of the camera is predicted by minimising the re-projection error to achieve a fast tracking performance, while the three-dimensional mesh is incrementally built by a dense zero mean normalised cross-correlation stereo-matching method to improve the accuracy of the surface reconstruction. The proposed system does not require any prior template or pre-operative scan and can infer the geometric information intra-operatively in real time. With the geometric information available, the proposed AR framework is able to interactively add annotations, localisation of tumours and vessels, and measurement labelling with greater precision and accuracy compared with the state-of-the-art approaches.
https://eprints.bournemouth.ac.uk/29496/
Source: Scopus
Real-time Geometry-Aware Augmented Reality in Minimally Invasive Surgery
Authors: Chen, L., Tang, W. and John, N.W.
Journal: the IET’s HealthCare Technology Letters Journal
Abstract:The potential of Augmented Reality (AR) technology to assist minimally invasive surgeries (MIS) lies in its computational performanceand accuracy in dealing with challenging MIS scenes. Even with the latest hardware and software technologies, achieving both real-timeand accurate augmented information overlay in MIS is still a formidable task. In this paper, we present a novel real-time AR frameworkfor MIS that achieves interactive geometric aware augmented reality in endoscopic surgery with stereo views. Our framework tracks themovement of the endoscopic camera and simultaneously reconstructs a dense geometric mesh of the MIS scene. The movement of the camerais predicted by minimising the re-projection error to achieve a fast tracking performance, while the 3D mesh is incrementally built by a densezero mean normalised cross correlation stereo matching method to improve the accuracy of the surface reconstruction. Our proposed systemdoes not require any prior template or pre-operative scan and can infer the geometric information intra-operatively in real-time. With thegeometric information available, our proposed AR framework is able to interactively add annotations, localisation of tumors and vessels,and measurement labeling with greater precision and accuracy compared with the state of the art approaches.
https://eprints.bournemouth.ac.uk/29496/
http://digital-library.theiet.org/content/journals/htl?origin=/htl
Source: Manual
Real-time Geometry-Aware Augmented Reality in Minimally Invasive Surgery
Authors: Chen, L., Tang, W. and John, N.W.
Journal: Healthcare Technology Letters
Volume: 4
Issue: 5
Pages: 163-167
ISSN: 2053-3713
Abstract:The potential of Augmented Reality (AR) technology to assist minimally invasive surgeries (MIS) lies in its computational performanceand accuracy in dealing with challenging MIS scenes. Even with the latest hardware and software technologies, achieving both real-timeand accurate augmented information overlay in MIS is still a formidable task. In this paper, we present a novel real-time AR frameworkfor MIS that achieves interactive geometric aware augmented reality in endoscopic surgery with stereo views. Our framework tracks themovement of the endoscopic camera and simultaneously reconstructs a dense geometric mesh of the MIS scene. The movement of the camerais predicted by minimising the re-projection error to achieve a fast tracking performance, while the 3D mesh is incrementally built by a densezero mean normalised cross correlation stereo matching method to improve the accuracy of the surface reconstruction. Our proposed systemdoes not require any prior template or pre-operative scan and can infer the geometric information intra-operatively in real-time. With thegeometric information available, our proposed AR framework is able to interactively add annotations, localisation of tumors and vessels,and measurement labeling with greater precision and accuracy compared with the state of the art approaches.
https://eprints.bournemouth.ac.uk/29496/
http://digital-library.theiet.org/content/journals/htl?origin=/htl
Source: BURO EPrints