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Concurrent Segmentation and Localization for Tracking of Surgical Instruments

Abstract · Mar 30, 2017 22:37 ·

cs-cv

Arxiv Abstract

  • Iro Laina
  • Nicola Rieke
  • Christian Rupprecht
  • Josué Page Vizcaíno
  • Abouzar Eslami
  • Federico Tombari
  • Nassir Navab

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.

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