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Detection of Lung Nodule Candidates in Chest Radiographs

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Pattern Recognition and Image Analysis (IbPRIA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4478))

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Abstract

This paper presents an automated method for the selection of a set of lung nodule candidates, which is the first stage of a computer-aided diagnosis system for the detection of pulmonary nodules. An innovative operator, called sliding band filter (SBF), is used for enhancing the lung field areas. In order to reduce the influence of the blood vessels near the mediastinum, this filtered image is multiplied by a mask that assigns to each lung field point an a priori probability of belonging to a nodule. The result is further processed with a watershed segmentation method that divides each lung field into a set of non-overlapping areas. Suspicious nodule locations are associated with the regions containing the highest regional maximum values. The proposed method, whose result is an ordered set of lung nodule candidate regions, was evaluated on the 247 images of the JSRT database with very promising results.

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Authors and Affiliations

  1. INEB - Instituto de Engenharia Biomédica, Laboratório de Sinal e Imagem; Campus FEUP (Faculdade de Engenharia da Universidade do Porto), Rua Roberto Frias, s/n, 4200-465 Porto, Portugal

    Carlos S. Pereira, Hugo Fernandes, Ana Maria Mendonça & Aurélio Campilho

  2. Universidade do Porto, Faculdade de Engenharia, DEEC,  

    Carlos S. Pereira, Ana Maria Mendonça & Aurélio Campilho

Authors
  1. Carlos S. Pereira
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  2. Hugo Fernandes
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  3. Ana Maria Mendonça
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  4. Aurélio Campilho
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Joan Martí José Miguel Benedí Ana Maria Mendonça Joan Serrat

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© 2007 Springer Berlin Heidelberg

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Pereira, C.S., Fernandes, H., Mendonça, A.M., Campilho, A. (2007). Detection of Lung Nodule Candidates in Chest Radiographs. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_22

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  • DOI: https://doi.org/10.1007/978-3-540-72849-8_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72848-1

  • Online ISBN: 978-3-540-72849-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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