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Detection of the Central Mass of Spiculated Lesions — Signature Normalisation and Model Data Aspects
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Detection of the Central Mass of Spiculated Lesions — Signature Normalisation and Model Data Aspects
Reyer Zwiggelaar7  , Christopher J. Taylor8 and Caroline M. E. Rubin9
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Division of Computer Science, University of Portsmouth, Portsmouth, UK |
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Wolfson Image Analysis Unit, University of Manchester, Manchester, UK |
| (9) |
Breast Screening Unit, Royal South Hants Hospital, Southampton, UK |
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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