Nuclei Segmentation of Cervical Cell Images Based on Intermediate Segment Qualifier

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The accurate nuclei segmentation of cervical cell images is a very vital step in automated cervical diseases diagnosis. However, segmentation challenges exist because of problems such as nuclei embedment into cytoplasm folding or overlapping areas, impurity interference, low contrast and nuclei variation in shape and size. These problems can cause the nuclei segmentation results not so ideal. This paper presents an automated method for cells nuclei detection in cervical cell images. We propose an intermediate segment qualifier to categorize the nuclei segmentation results after the nuclei segmentation based on the integration of convolutional neural network and simple linear iterative clustering superpixel method. Then we apply a gradient vector flow snake model for further refinement. We evaluate the proposed method using the ISBI 2014 challenge dataset. In the experiments, we demonstrate that our method performs well and is preferable to the state-of-the-art approaches.

Original languageEnglish
Title of host publication2018 24th International Conference on Pattern Recognition, ICPR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3941-3946
Number of pages6
ISBN (Electronic)9781538637883
DOIs
Publication statusPublished - 2018 Nov 26
Externally publishedYes
Event24th International Conference on Pattern Recognition, ICPR 2018 - Beijing, China
Duration: 2018 Aug 202018 Aug 24

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume2018-August
ISSN (Print)1051-4651

Other

Other24th International Conference on Pattern Recognition, ICPR 2018
CountryChina
CityBeijing
Period18/8/2018/8/24

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Cells
Impurities
Neural networks
Experiments

Keywords

  • cervical cell image
  • cervical diseases
  • image segmentation
  • intermediate segment qualifier
  • nuclei segmentation

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Wang, R., & Kamata, S. (2018). Nuclei Segmentation of Cervical Cell Images Based on Intermediate Segment Qualifier. In 2018 24th International Conference on Pattern Recognition, ICPR 2018 (pp. 3941-3946). [8546215] (Proceedings - International Conference on Pattern Recognition; Vol. 2018-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPR.2018.8546215

Nuclei Segmentation of Cervical Cell Images Based on Intermediate Segment Qualifier. / Wang, Rui; Kamata, Seiichiro.

2018 24th International Conference on Pattern Recognition, ICPR 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 3941-3946 8546215 (Proceedings - International Conference on Pattern Recognition; Vol. 2018-August).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wang, R & Kamata, S 2018, Nuclei Segmentation of Cervical Cell Images Based on Intermediate Segment Qualifier. in 2018 24th International Conference on Pattern Recognition, ICPR 2018., 8546215, Proceedings - International Conference on Pattern Recognition, vol. 2018-August, Institute of Electrical and Electronics Engineers Inc., pp. 3941-3946, 24th International Conference on Pattern Recognition, ICPR 2018, Beijing, China, 18/8/20. https://doi.org/10.1109/ICPR.2018.8546215
Wang R, Kamata S. Nuclei Segmentation of Cervical Cell Images Based on Intermediate Segment Qualifier. In 2018 24th International Conference on Pattern Recognition, ICPR 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 3941-3946. 8546215. (Proceedings - International Conference on Pattern Recognition). https://doi.org/10.1109/ICPR.2018.8546215
Wang, Rui ; Kamata, Seiichiro. / Nuclei Segmentation of Cervical Cell Images Based on Intermediate Segment Qualifier. 2018 24th International Conference on Pattern Recognition, ICPR 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 3941-3946 (Proceedings - International Conference on Pattern Recognition).
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