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Evaluation of Contrast Enhancement Filters for Lung Nodule Detection

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Image Analysis and Recognition (ICIAR 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4633))

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Abstract

The aim of this paper is to evaluate and compare the performance of three convergence index (CI) filters when applied to the enhancement of chest radiographs, aiming at the detection of lung nodules. One of these filters, the sliding band filter (SBF), is the proposal of an innovative operator, while the other two CI class members, the iris filter (IF) and the adaptive ring filter (ARF), are already known in this application. To demonstrate the adequacy of the new filter for the enhancement of chest x-ray images, we calculated several figures of merit with the goal of comparing (i) the contrast enhancement capability of the filters, and (ii) the behavior of the filters for the detection of lung nodules. The results obtained for 154 images with nodules of the JSRT database show that the SBF outperforms both the IF and ARF. The proposed filter demonstrated to be a promising enhancement method, thus justifying its use in the first stage of a computer-aided diagnosis system for the detection of lung nodules.

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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, 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. Ana Maria Mendonça
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  3. Aurélio Campilho
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Mohamed Kamel Aurélio Campilho

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© 2007 Springer-Verlag Berlin Heidelberg

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Pereira, C.S., Mendonça, A.M., Campilho, A. (2007). Evaluation of Contrast Enhancement Filters for Lung Nodule Detection. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2007. Lecture Notes in Computer Science, vol 4633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74260-9_78

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  • DOI: https://doi.org/10.1007/978-3-540-74260-9_78

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74258-6

  • Online ISBN: 978-3-540-74260-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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