26 September 2013 Real time contact-free and non-invasive tracking of the human skull: first light and initial validation
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In an increasing number of fields in medicine, precise and fast localisation of bony targets inside the body is essential. Up to now, exact localisation in the operation room can either be done with invasive methods like X-ray imaging and electromagnetic tracking systems, with volumetric ultrasound or by fixing the target in place. In this work, we present a new technology to directly track the position of the human skull through tissue in real time using infrared lasers. To achieve this, an experimental setup has been developed to precisely target a position on a subject's skin with an 850nm laser. The primary reflection on the skin is triangulated using a high-speed camera. Additionally, the reflections as well as in-tissue scattering are recorded with an in-beam setup of a NIR sensitive high-speed and high-resolution camera. Consequently, it is possible to record the scattering patterns specific to the composition of the tissue at the target. We have recorded MRI data of two test subjects (voxel size 0.15 x 0.15 x 1mm3) and extracted the soft tissue thickness with a semi-automatic segmentation approach. The MRI data was validated using force-controlled 2D ultrasound (tracked by an optical tracking system), from which soft tissue thickness was segmented manually. Optical measurements and MRI data were registered to determine soft tissue thickness for each measured laser target and finally used to train a support vector regression machine. Using the optical setup, we succeeded in computing the soft tissue thickness on the subjects' foreheads with sub-millimetre accuracy.
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Floris Ernst, Floris Ernst, Ralf Bruder, Ralf Bruder, Tobias Wissel, Tobias Wissel, Patrick Stüber, Patrick Stüber, Benjamin Wagner, Benjamin Wagner, Achim Schweikard, Achim Schweikard, "Real time contact-free and non-invasive tracking of the human skull: first light and initial validation", Proc. SPIE 8856, Applications of Digital Image Processing XXXVI, 88561G (26 September 2013); doi: 10.1117/12.2024851; https://doi.org/10.1117/12.2024851

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