PublicationDetail

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

N. Rieke, D. J. Tan , F. Tombari, J. Page Vizcaino, C. Amat di San Filippo, A. Eslami, N. Navab
Real-Time Online Adaption for Robust Instrument Tracking and Pose Estimation
Proceedings of the 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Athens, Greece, October 2016 (bib)

We propose a novel method for instrument tracking in Retinal Microsurgery (RM) which is apt to withstand the challenges of RM visual sequences in terms of varying illumination conditions and blur. At the same time, the method is general enough to deal with different background and tool appearances. The proposed approach relies on two random forests to, respectively, track the surgery tool and estimate its pose. Robustness to photometric distortions and blur is provided by a specific online refinement stage of the offline trained forest, which makes our method also capable of generalizing to unseen backgrounds and tools. In addition, a peculiar framework for merging together the predictions of tracking and pose is employed to improve the overall accuracy. Remarkable advantages in terms of accuracy over the state-of-the-art are shown on two public benchmarks.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.



Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif