Segmentation of Pulmonary Nodules in CT Images Using the Sliding Band Filter

  • Joana RochaEmail author
  • António Cunha
  • Ana Maria Mendonça
Conference paper
Part of the IFMBE Proceedings book series (IFMBE, volume 76)


This paper proposes a conventional approach for pulmonary nodule segmentation, that uses the Sliding Band Filter to estimate the center of the nodule, and consequently the filter’s support points, matching the initial border coordinates. This preliminary segmentation is then refined to try to include mainly the nodular area, and no other regions (e.g. vessels and pleural wall). The algorithm was tested on 2653 nodules from the LIDC database and achieved a Dice score of 0.663, yielding similar results to the ground truth reference, and thus being a promising tool to promote early lung cancer screening and improve nodule characterization.


Lung Nodule Segmentation Sliding band filter 


Conflict of Interest

The authors declare no conflict of interest. This work is financed by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project: UID/EEA/50014/2019.


  1. 1.
    Torre, L.A., Siegel, R.L., Jemal, A.: Lung cancer statistics. In: Lung Cancer and Personalized Medicine, pp. 1–19. Springer, Cham (2016). Scholar
  2. 2.
    Litjens, G., Kooi, T., Bejnordi, B.E., Setio, A.A.A., Ciompi, F., Ghafoorian, M., Sánchez, C.I.: A survey on deep learning in medical image analysis. Med. Image Anal. 42, 60–88 (2017). Scholar
  3. 3.
    Pereira, C.S., Mendonça, A.M., Campilho, A.: Evaluation of contrast enhancement filters for lung nodule detection. In: International Conference Image Analysis and Recognition, pp. 878–888. Springer, Heidelberg, August 2007.
  4. 4.
    Dashtbozorg, B., Mendonça, A.M., Campilho, A.: Optic disc segmentation using the sliding band filter. Comput. Biol. Med. 56, 1–12 (2015). Scholar
  5. 5.
    Quelhas, P., Marcuzzo, M., Mendonça, A.M., Campilho, A.: Cell nuclei and cytoplasm joint segmentation using the sliding band filter. IEEE Trans. Med. Imaging 29(8), 1463–1473 (2010). Scholar
  6. 6.
    Shakibapour, E., Cunha, A., Aresta, G., Mendonça, A.M., Campilho, A.: An unsupervised metaheuristic search approach for segmentation and volume measurement of pulmonary nodules in lung CT scans. Expert Syst. Appl. 119, 415–428 (2019). Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Joana Rocha
    • 1
    • 2
    Email author
  • António Cunha
    • 2
    • 3
  • Ana Maria Mendonça
    • 1
    • 2
  1. 1.Faculdade de EngenhariaUniversidade do PortoPortoPortugal
  2. 2.INESC TEC – INESC Technology and SciencePortoPortugal
  3. 3.Universidade de Trás-os-Montes e Alto DouroVila RealPortugal

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