Abstract
We describe a method for labelling image structure based on non-linear scale-orientation signatures which can be used as a basis for robust pixel classification. The effect of normalisation of the signatures is discussed as a means to improve classification robustness with respect to grey-level variations. In addition, model data selection and scale normalisation are investigated as a means to improve the robustness of detection with respect to the scale of structures.
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References
Zwiggelaar, R., et al.: Model-based detection of spiculated lesions in mammograms. Medical Image Analysis 3 (1999) 39–62
Jolliffe, I.T.: Principal Component Analysis. Springer Verlag (1986)
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© 1999 Springer-Verlag Berlin Heidelberg
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Zwiggelaar, R., Taylor, C.J., Rubin, C.M.E. (1999). Detection of the Central Mass of Spiculated Lesions — Signature Normalisation and Model Data Aspects. In: Kuba, A., Šáamal, M., Todd-Pokropek, A. (eds) Information Processing in Medical Imaging. IPMI 1999. Lecture Notes in Computer Science, vol 1613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48714-X_37
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DOI: https://doi.org/10.1007/3-540-48714-X_37
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66167-2
Online ISBN: 978-3-540-48714-2
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