Model Based 3D Segmentation and OCT Image Undistortion of Percutaneous Implants [chapter]

Oliver Müller, Sabine Donner, Tobias Klinder, Ralf Dragon, Ivonne Bartsch, Frank Witte, Alexander Krüger, Alexander Heisterkamp, Bodo Rosenhahn
<span title="">2011</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Optical Coherence Tomography (OCT) is a noninvasive imaging technique which is used here for in vivo biocompatibility studies of percutaneous implants. A prerequisite for a morphometric analysis of the OCT images is the correction of optical distortions caused by the index of refraction in the tissue. We propose a fully automatic approach for 3D segmentation of percutaneous implants using Markov random fields. Refraction correction is done by using the subcutaneous implant base as a prior for
more &raquo; ... del based estimation of the refractive index using a generalized Hough transform. Experiments show the competitiveness of our algorithm towards manual segmentations done by experts. This work has been partially funded by the DFG within the excellence cluster RE-BIRTH.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-23626-6_56">doi:10.1007/978-3-642-23626-6_56</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3vks5j6bbnhe3n2nazsxyd2lde">fatcat:3vks5j6bbnhe3n2nazsxyd2lde</a> </span>
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