Estimation of surgical tool pose is essential for surgical image guidance. Near real-time position and angle estimation is crucial, for example, for intraoperative optical coherence tomography tracking in retinal microsurgery. The current state-of-the-art algorithm for surgical tool tracking in posterior eye surgery was first introduced by Alsheakhali et al.1 We propose Dual Color Space Algorithm - an improved tool segmentation method based on combined color space masks, set thresholds, a shadow-insensitive detector for the tool edge, and more robust detection of the tip of the surgical tools. The presented algorithms are benchmarked on a series of manually annotated images from posterior eye surgery video. The video frames suffer from the confounding effect of the tool’s shadow and spot illumination occurring several times. A severalfold improvement in the algorithm’s accuracy is reported.
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