Circular Shape Prior in Efficient Graph Based Image Segmentation to Segment Nucleus

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    3 Citations (Scopus)

    Abstract

    A graph based segmentation approach is proposed in this study to segment nucleus from cytology images. This approach utilizes a novel method applying weighted circular shape prior adaptively in efficient graph based image segmentation. The proposed method was evaluated by segmenting nucleus from two public Pap smear image datasets: ISBI 2014 challenge dataset (945 images) and DTU/Herlev intermediate squamous cell dataset (70 images). Segmentation results of the proposed method outperformed the standard one in terms of Dice similarity coefficient, pixel-based precision and recall, Hausdorff distance, and H t metric. Quantitative measures and visual results indicate that the proposed technique produces better nucleus boundaries.

    Original languageEnglish
    Title of host publication2018 International Conference on Digital Image Computing
    Subtitle of host publicationTechniques and Applications, DICTA 2018
    EditorsMark Pickering, Lihong Zheng, Shaodi You, Ashfaqur Rahman, Manzur Murshed, Md Asikuzzaman, Ambarish Natu, Antonio Robles-Kelly, Manoranjan Paul
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Number of pages8
    ISBN (Electronic)9781538666029
    DOIs
    Publication statusPublished - 16 Jan 2019
    Event2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018 - Canberra, Australia
    Duration: 10 Dec 201813 Dec 2018

    Publication series

    Name2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018

    Conference

    Conference2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018
    CountryAustralia
    CityCanberra
    Period10/12/1813/12/18

    Keywords

    • circular shape prior
    • graph based image segmentation
    • minimum spanning tree
    • nucleus segmentation

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