Inflammatory Cell Extraction and Nuclei Detection in Pap Smear Images

The automated diagnosis of cervical cancer in Pap smear images is a difficult though extremely important procedure. In order to obtain reliable diagnostic information, the nuclei and their characteristics must be correctly identified and evaluated. However, the presence of inflammatory and overlappi...

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Published inInternational journal of e-health and medical communications Vol. 6; no. 2; pp. 27 - 43
Main Authors Riana, Dwiza, Plissiti, Marina E, Nikou, Christophoros, Widyantoro, Dwi H, Mengko, Tati Latifah R, Kalsoem, Oemie
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.04.2015
Subjects
Algorithms
Cancer
Cervical cancer
Diagnostic systems
Extraction
Health aspects
Image detection
Medical imaging
Nuclei
Nuclei (cytology)
Pap test
Segmentation
Smear
Women
Indonesia
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Summary:The automated diagnosis of cervical cancer in Pap smear images is a difficult though extremely important procedure. In order to obtain reliable diagnostic information, the nuclei and their characteristics must be correctly identified and evaluated. However, the presence of inflammatory and overlapping cells in these images complicates the detection process. In this work, a segmentation algorithm is developed to extract the inflammatory cells and enable accurate nuclei detection. The proposed algorithm is based on the combination of gray level thresholding and the definition of a distance rule, which entails in the identification of inflammatory cells. The results indicate that our method significantly simplifies the nuclei detection process, as it reduces the number of inflammatory cells that may interfere.
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ISSN:1947-315X
1947-3168
DOI:10.4018/IJEHMC.2015040103