Abstract
We present a spatio-temporal filter for real-time noise reduction of strongly corrupted X-ray image sequences. It possesses efficient noise reduction while, at the same time, preventing typical artifacts of state-of-the-art methods. Decisive for these features are, in particular, innovative motion detection as well as noise-adaptive filter parametrization. Motion detection based on twofold signed binarization proved to be a powerful method for pixelwise separation of motion and strong noise. Drawbacks of threshold determination by Euler curve analysis as applied previously were eliminated by integration of signal-dependent noise estimation.
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Hensel M, Lundt B, Pralow T, Grigat RR. Robust and Fast Estimation of Signal-Dependent Noise in Medical X-Ray Image Sequences. In: Procs BVM; 2006.
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Hensel, M., Pralow, T., Grigat, RR. (2006). LAST Filter for Artifact-Free Noise Reduction of Fluoroscopic Sequences in Real-Time. In: Handels, H., Ehrhardt, J., Horsch, A., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2006. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32137-3_4
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DOI: https://doi.org/10.1007/3-540-32137-3_4
Publisher Name: Springer, Berlin, Heidelberg
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