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Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience

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

Abstract

Purpose

A computerized classification scheme to recognize breast parenchymal patterns in whole breast ultrasound (US) images was developed. A preliminary evaluation of the system performance was performed.

Methods

Breast parenchymal patterns were classified into three categories: mottled pattern (MP), intermediate pattern (IP), and atrophic pattern (AP). Each classification was defined as proposed by an experienced physician. A total of 281 image features were extracted from a volume of interest which was automatically segmented. Canonical discriminant analysis with stepwise feature selection was employed for the classification of the parenchymal patterns.

Results

The classification scheme accuracy was computed to be 83.3% (10/12 cases) in MP cases, 91.7% (22/24 cases) in IP cases, 92.9% (13/14 cases) in AP cases, and 90.0% (45/50 cases) in all the cases.

Conclusions

The feasibility of an automated ultrasonography classifier for parenchymal patterns was demonstrated with promising results in whole breast US images.

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Authors and Affiliations

  1. Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, Yanagido, Gifu, Japan

    Yuji Ikedo, Takeshi Hara, Gobert Lee & Hiroshi Fujita

  2. Department of Mammary Gland, Chunichi Hospital, Naka-ku, Nagoya, Japan

    Takako Morita

  3. Technology Education, Faculty of Education, Gifu University, Yanagido, Gifu, Japan

    Daisuke Fukuoka

  4. Center of Medical Ultrasonics, Dokkyo Medical University School of Medicine, Shimotsuga-gun, Tochigi, Japan

    Etsuo Takada

  5. Department of Radiology, National Hospital Organization Nagoya Medical Center, Naka-ku, Nagoya, Japan

    Tokiko Endo

Authors
  1. Yuji Ikedo
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  2. Takako Morita
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  3. Daisuke Fukuoka
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  4. Takeshi Hara
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  5. Gobert Lee
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  6. Hiroshi Fujita
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  7. Etsuo Takada
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  8. Tokiko Endo
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Correspondence to Yuji Ikedo.

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Ikedo, Y., Morita, T., Fukuoka, D. et al. Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience. Int J CARS 4, 299–306 (2009). https://doi.org/10.1007/s11548-009-0295-0

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  • DOI: https://doi.org/10.1007/s11548-009-0295-0

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