Segmentation of cervical nuclei using SLIC and pairwise regional contrast

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

A framework to detect and segment nuclei from cervical cytology images is proposed in this study. Poor contrast, spurious edges, degree of overlap, and intensity inhomogeneity make the nuclei segmentation task more complex in overlapping cell images. The proposed technique segments cervical nuclei by merging over-segmented SLIC superpixel regions using a novel region merging criteria based on pairwise regional contrast and image gradient contour evaluations. The framework was evaluated using the first overlapping cervical cytology image segmentation challenge - ISBI 2014 dataset. The result shows that the proposed framework outperforms the state-of-the-art algorithms in nucleus detection and segmentation accuracies.

Original languageEnglish
Title of host publication2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
EditorsJim Patton
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3422-3425
Number of pages4
ISBN (Electronic)9781538636466
DOIs
Publication statusPublished - 26 Oct 2018
Event2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) -
Duration: 18 Jul 2018 → …

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2018-July
ISSN (Print)1557-170X

Conference

Conference2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Period18/07/18 → …

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