Circular shape prior in efficient graph based image segmentation to segment nucleus

Ratna Saha, Mariusz Bajger, Gobert Lee

Research output: Contribution to conferencePaperpeer-review

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 Ht metric. Quantitative measures and visual results indicate that the proposed technique produces better nucleus boundaries.
Original languageEnglish
Pages1-8
Number of pages8
DOIs
Publication statusPublished - 2018
Event2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA) - Canberra, Australia
Duration: 10 Dec 201813 Dec 2018

Conference

Conference2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
Abbreviated titleDICTA
CountryAustralia
CityCanberra
Period10/12/1813/12/18

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