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A Fuzzy-based Automated Cells Detection System for Color Pap Smear Tests –-FACSDS–

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Book cover Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 220))

Abstract

There is a compelling need for automated cervical smear screening systems to improve the quality and cost/efficiency screening rate. Computer-assisted devices can reduce false negative Pap smear interpretations using computerized systems to assist the cytotechnologist in identifying Pap smear abnormalities and providing added value in their ability to consistently and objectively analyze all cells on slides without fatigue. However, automation of the process is a challenging problem due to the large variability in conventional Pap smears exhibiting no standard appearance and tremendous amount of data to be processed. Moreover, smear diagnostic may be obscured by benign conditions, overlapping cells, debris, inflammation, and no uniform staining.

Here we propose an efficient and fast Fuzzy-based Automated Cells Screening Detection System -FACSDS-, which can be useful for future Automatic Cells Screening System ACSS-. Because of detecting abnormal cells in a Pap smear can be refereed to as a “rare” event problem due to the normal cells and artifacts outnumber the intraepithelial lesions, the proposed algorithm has been divided into two steps. At first step the Areas of Interest AOI-, or best areas for screening in the smear, are detected and the degree to which these areas are interesting is given by means their evaluation goodness degree. At second step the AOIs are analyzed, taking into account their evaluation goodness degree, for detecting the cell nucleus. First step is carried out on monochrome images obtained using a 2.5X objective, and the results obtained have provided a high concordance degree with the cytotechnologist evaluation. The automatic system implemented at second step for detecting the nuclei is based on color information. We have considered color images because cells’ nuclei appear as dark regions within the images, hardly detected on monochrome images. Moreover, as color-order systems based on perceptual variables are somehow correlated with human being’s color perception, and their coordinates are highly independent, what makes possible to treat achromatic and chromatic information separately, the proposed algorithm first convert RGB into Hue, Saturation and Intensity (HSI) color components. In addition, we make use of fuzzy techniques to face up the problems due to low saturation and illumination.

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Authors
  1. Pilar Sobrevilla
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  2. Eduard Montseny
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  3. Enrique Lerma
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Editor information

Editors and Affiliations

  1. Department of Automatics and Computation, Universidad Pública de Navarra, Campus Arrosadia s/n, 31006 Pamplona, Spain

    Humberto Bustince

  2. Department of Computer Science and Artificial Intelligence (DECSAI), University of Granada, Periodista Daniel Saucedo Aranda s/n, 18071 Granada, Spain

    Francisco Herrera

  3. Faculty of Mathematics, Universidad Complutense, Plaza de las Ciencias 3, 28040 Madrid, Spain

    Javier Montero

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© 2008 Springer-Verlag Berlin Heidelberg

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Sobrevilla, P., Montseny, E., Lerma, E. (2008). A Fuzzy-based Automated Cells Detection System for Color Pap Smear Tests –-FACSDS–. In: Bustince, H., Herrera, F., Montero, J. (eds) Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Studies in Fuzziness and Soft Computing, vol 220. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73723-0_34

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  • DOI: https://doi.org/10.1007/978-3-540-73723-0_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73722-3

  • Online ISBN: 978-3-540-73723-0

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