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Automatic classification of lung nodules on MDCT images with the temporal subtraction technique

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

Abstract

Purpose

A temporal subtraction (TS) image is obtained by subtracting a previous image, which is warped to match the structures of the previous image and the related current image. The TS technique removes normal structures and enhances interval changes such as new lesions and substitutes in existing abnormalities from a medical image. However, many artifacts remaining on the TS image can be detected as false positives.

Method

This paper presents a novel automatic segmentation of lung nodules using the Watershed method, multiscale gradient vector flow snakes and a detection method using the extracted features and classifiers for small lung nodules (20 mm or less).

Result

Using the proposed method, we conduct an experiment on 30 thoracic multiple-detector computed tomography cases including 31 small lung nodules.

Conclusion

The experimental results indicate the efficiency of our segmentation method.

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Acknowledgements

This study was funded by KAKENHI of MEXT-Japan (26108009;16809746).

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Authors and Affiliations

  1. Kyushu Institute of Technology, Fukuoka, Japan

    Yuriko Yoshino, Takahiro Miyajima, Huimin Lu, Jookooi Tan & Hyoungseop Kim

  2. University of Occupational & Environment Health, Fukuoka, Japan

    Seiichi Murakami & Takatoshi Aoki

  3. National Institute of Technology, Oshima College, Yamaguchi, Japan

    Rie Tachibana

  4. Yamaguchi University, Yamaguchi, Japan

    Yasushi Hirano & Shoji Kido

Authors
  1. Yuriko Yoshino
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  2. Takahiro Miyajima
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  3. Huimin Lu
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  4. Jookooi Tan
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  5. Hyoungseop Kim
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  6. Seiichi Murakami
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  7. Takatoshi Aoki
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  8. Rie Tachibana
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  9. Yasushi Hirano
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  10. Shoji Kido
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Corresponding author

Correspondence to Huimin Lu.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

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Yoshino, Y., Miyajima, T., Lu, H. et al. Automatic classification of lung nodules on MDCT images with the temporal subtraction technique. Int J CARS 12, 1789–1798 (2017). https://doi.org/10.1007/s11548-017-1598-1

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  • DOI: https://doi.org/10.1007/s11548-017-1598-1

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