Abstract
A novel method for detection of thin lines in strongly noise-corrupted images is presented. The method can be applied e.g. for guide wire detection in X-ray fluoroscopy sequences. In a first step, the responses of a set of angular separable filters are calculated and the maximum of the filter responses is taken. Application of a subsampling scheme allows to reduce the computational effort. In a second step, a flood filling algorithm is used to eliminate worm-like artifacts arising from random line structures in the noise. Depending on the line curvature, signal-to-noise ratio (SNR) improvements of 27 dB have been achieved.
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References
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© 2005 Springer-Verlag Berlin Heidelberg
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Kunz, D., Schweiger, B. (2005). Line Detection in Strongly Noise-Corrupted Images. In: Meinzer, HP., Handels, H., Horsch, A., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2005. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-26431-0_11
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DOI: https://doi.org/10.1007/3-540-26431-0_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25052-4
Online ISBN: 978-3-540-26431-6
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