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

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

6 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
Number of pages8
ISBN (Electronic)9781538666029
DOIs
Publication statusPublished - 16 Jan 2019
Event2018 International Conference on Digital Image Computing: Techniques and Applications - 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
Abbreviated titleDICTA 2018
Country/TerritoryAustralia
CityCanberra
Period10/12/1813/12/18

Keywords

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

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