I. Laina, N. Rieke, C. Rupprecht, J. Page Vizcaino, A. Eslami, F. Tombari, N. Navab Concurrent Segmentation and Localization for Tracking of Surgical Instruments Accepted to Proceedings of the 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec, Canada, September 2017. A pre-print version is available online at arXiv. The first two authors contribute equally to this paper. (bib)
	Instrument tracking is an essential requirement for various computer-assisted interventions. To overcome problems such as specular reflection and motion blur, we propose a novel method that takes advantage of the interdependency between localization and segmentation of the tool. In particular, we reformulate the 2D pose estimation as a heatmap regression and thereby enable a robust, concurrent regression of both tasks. Throughout experimental results, we demonstrate that this modeling leads to a significantly higher accuracy than directly regressing the tool's coordinates. The performance is compared to state-of-the-art on a Retinal Microsurgery benchmark and the EndoVis? Challenge.
	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.