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Feature Extraction from a Signature Based on the Turning Angle Function for the Classification of Breast Tumors

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Abstract

Malignant breast tumors and benign masses appear in mammograms with different shape characteristics: the former usually have rough, spiculated, or microlobulated contours, whereas the latter commonly have smooth, round, oval, or macrolobulated contours. Features that characterize shape roughness and complexity can assist in distinguishing between malignant tumors and benign masses. Signatures of contours may be used to analyze their shapes. We propose to use a signature based on the turning angle function of contours of breast masses to derive features that capture the characteristics of shape roughness as described above. We propose methods to derive an index of the presence of convex regions (XR TA ), an index of the presence of concave regions (VR TA ), an index of convexity (CX TA ), and two measures of fractal dimension (FD TA and FDd TA ) from the turning angle function. The methods were tested with a set of 111 contours of 65 benign masses and 46 malignant tumors with different parameters. The best classification accuracies in discriminating between benign masses and malignant tumors, obtained for XR TA , VR TA , CX TA , FD TA , and FDd TA in terms of the area under the receiver operating characteristics curve, were 0.92, 0.92, 0.93, 0.93, and, 0.92, respectively.

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Acknowledgment

This work was supported by the Conselho Nacional Desenvolvimento Científıco e Tecnológico of Brazil, and the Catalyst Program of Research Services, University of Calgary. We thank Fábio José Ayres, University of Calgary for assistance with the ROC procedures.

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Authors and Affiliations

  1. Faculdade de Computação, Universidade Federal de Uberlândia, Av. João Naves de Ávila 2121 38, 400-902, Minas Gerais, Brazil

    Denise Guliato, Juliano D. de Carvalho & Sérgio A. Santiago

  2. Department of Electrical and Computer Engineering, University of Calgary Schulich School of Engineering, 2500 University Drive N. W, Calgary, Alberta, Canada, T2N 1N4

    Rangaraj M. Rangayyan

Authors
  1. Denise Guliato
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  2. Juliano D. de Carvalho
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  3. Rangaraj M. Rangayyan
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  4. Sérgio A. Santiago
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Correspondence to Denise Guliato.

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Guliato, D., de Carvalho, J.D., Rangayyan, R.M. et al. Feature Extraction from a Signature Based on the Turning Angle Function for the Classification of Breast Tumors. J Digit Imaging 21, 129–144 (2008). https://doi.org/10.1007/s10278-007-9069-9

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  • DOI: https://doi.org/10.1007/s10278-007-9069-9

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