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A pilot study of architectural distortion detection in mammograms based on characteristics of line shadows

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Objective

We present herein a novel algorithm for architectural distortion detection that utilizes the point convergence index with the likelihood of lines (e.g., spiculations) relating to architectural distortion.

Materials and methods

Validation was performed using 25 computed radiography (CR) mammograms, each of which has an architectural distortion with radiating spiculations. The proposed method comprises five steps. First, the lines were extracted on mammograms, such as spiculations of architectural distortion as well as lines in the mammary gland. Second, the likelihood of spiculation for each extracted line was calculated. In the third step, point convergence index weighted by this likelihood was evaluated at each pixel to enhance distortion only. Fourth, local maxima of the index were extracted as candidates for the distortion, then classified based on nine features in the last step.

Results

Point convergence index without the proposed likelihood generated 84.48/image false-positives (FPs) on average. Conversely, the proposed index succeeded in decreasing this number to 12.48/image on average when sensitivity was 100%. After the classification step, number of FPs was reduced to 0.80/image with 80.0% sensitivity.

Conclusion

Combination of the likelihood of lines with point convergence index is effective in extracting architectural distortion with radiating spiculations.

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Abbreviations

AD:

Architectural distortion

CAD:

Computer-assisted detection/diagnosis

CR:

Computed radiography

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Authors and Affiliations

  1. Department of Radiology, The University of Tokyo Hospital, 7-3-1 Hongo Bunkyo-ku, Tokyo, Japan

    Mitsutaka Nemoto

  2. Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, Japan

    Soshi Honmura, Akinobu Shimizu, Daisuke Furukawa & Hidefumi Kobatake

  3. Department of Radiology, International University of Health and Welfare Mita Hospital, 1-4-3 Mita, Minato-ku, Tokyo, Japan

    Shigeru Nawano

Authors
  1. Mitsutaka Nemoto
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  2. Soshi Honmura
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  3. Akinobu Shimizu
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  4. Daisuke Furukawa
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  5. Hidefumi Kobatake
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  6. Shigeru Nawano
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Correspondence to Mitsutaka Nemoto.

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Nemoto, M., Honmura, S., Shimizu, A. et al. A pilot study of architectural distortion detection in mammograms based on characteristics of line shadows. Int J CARS 4, 27–36 (2009). https://doi.org/10.1007/s11548-008-0267-9

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  • DOI: https://doi.org/10.1007/s11548-008-0267-9

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