Abstract
We describe a method for labelling image structure based on scale-orientation signatures. These signatures provide a rich and stable description of local structure and can be used as a basis for robust pixel classification. We use a multi-scale directional recursive median filtering technique to obtain local scale-orientation signatures. Our results show that the new method of representation is robust to the presence of both random and structural noise. We demonstrate application to synthetic images containing lines and blob-like features and to mammograms containing abnormal masses. Quantitative results are presented, using both linear and non-linear classification methods.
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Keywords
- Principal Component Analysis Model
- Background Texture
- Linear Classification
- Temporal Subtraction
- False Positive Fraction
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© 1998 Springer-Verlag Berlin Heidelberg
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Zwiggelaar, R., Taylor, C.J. (1998). Abnormal masses in mammograms: Detection using scale-orientation signatures. In: Wells, W.M., Colchester, A., Delp, S. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI’98. MICCAI 1998. Lecture Notes in Computer Science, vol 1496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0056242
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DOI: https://doi.org/10.1007/BFb0056242
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