22 June 2015 Feasibility test of line sensors for optical tissue thickness estimation
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Purpose Line sensors are cheap, fast and have high quantum effciencies. Here, we investigate whether these sensors can replace an area image sensor for the purpose of tissue thickness measurements. Material and Methods As part of a subject study high dynamic range (HDR) images of three subjects were acquired with an area image sensor. To simulate a line sensor as realistic as possible single or multiple lines were extracted from these HDR images. Thereby, horizontally extracted lines correspond to a parallel orientation of the line sensor relative to the incident angle of a laser beam. Vertically extracted lines correspond to an orthogonal orientation. Then, optical features were determined and converted into a tissue thickness using a machine learning algorithm. Results For the tested subjects the worst root mean square error (RMSE) of the learning process was 0:385 mm. The best RMSE was 0:222 mm. For all subjects, the mean RMSE and the standard deviation of RMSE values decreases with a larger number of extracted lines. The orientation of the line sensor turned out to be important for the RMSE. Vertically oriented line sensors achieve lower RMSEs than horizontally oriented sensors because of the influence of the incident angle. Furthermore, the head-pose of the subject seems to be important for the accuracy. Conclusion Line sensors deliver comparable results to previously analysed area image sensors. Nevertheless, the scattering of the values is higher and the size and orientation of the sensor and the head-pose have an influence on the RMSE of the learning process. Therefore, line sensors are feasible for tissue thickness estimation but they are a trade-off between accuracy and speed.
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Patrick Stüber, Patrick Stüber, Tobias Wissel, Tobias Wissel, Benjamin Wagner, Benjamin Wagner, Achim Schweikard, Achim Schweikard, Floris Ernst, Floris Ernst, } "Feasibility test of line sensors for optical tissue thickness estimation", Proc. SPIE 9529, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials II, 95291C (22 June 2015); doi: 10.1117/12.2184815; https://doi.org/10.1117/12.2184815


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