@inproceedings{ae1a7119a25d42dba48d696283f16e90,
title = "Circular Shape Prior in Efficient Graph Based Image Segmentation to Segment Nucleus",
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. ",
keywords = "circular shape prior, graph based image segmentation, minimum spanning tree, nucleus segmentation",
author = "Ratna Saha and Mariusz Bajger and Gobert Lee",
year = "2019",
month = jan,
day = "16",
doi = "10.1109/DICTA.2018.8615768",
language = "English",
series = "2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018",
publisher = "Institute of Electrical and Electronics Engineers",
editor = "Mark Pickering and Lihong Zheng and Shaodi You and Ashfaqur Rahman and Manzur Murshed and Md Asikuzzaman and Ambarish Natu and Antonio Robles-Kelly and Manoranjan Paul",
booktitle = "2018 International Conference on Digital Image Computing",
address = "United States",
note = "2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018 ; Conference date: 10-12-2018 Through 13-12-2018",
}