Nuclei Segmentation using a Level Set Active Contour Method and Spatial Fuzzy C-means Clustering

Ravali Edulapuram, R. Joe Stanley, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, William V. Stoecker, Jason Hagerty

Abstract

Digitized histology images are analyzed by expert pathologists in one of several approaches to assess pre-cervical cancer conditions such as cervical intraepithelial neoplasia (CIN). Many image analysis studies focus on detection of nuclei features to classify the epithelium into the CIN grades. The current study focuses on nuclei segmentation based on level set active contour segmentation and fuzzy c-means clustering methods. Logical operations applied to morphological post-processing operations are used to smooth the image and to remove non-nuclei objects. On a 71-image dataset of digitized histology images (where the ground truth is the epithelial mask which helps in eliminating the non epithelial regions), the algorithm achieved an overall nuclei segmentation accuracy of 96.47%. We propose a simplified fuzzy spatial cost function that may be generally applicable for any n-class clustering problem of spatially distributed objects.

References

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Paper Citation


in Harvard Style

Edulapuram R., Stanley R., Long R., Antani S., Thoma G., Zuna R., Stoecker W. and Hagerty J. (2017). Nuclei Segmentation using a Level Set Active Contour Method and Spatial Fuzzy C-means Clustering . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 195-202. DOI: 10.5220/0006136201950202


in Bibtex Style

@conference{visapp17,
author={Ravali Edulapuram and R. Joe Stanley and Rodney Long and Sameer Antani and George Thoma and Rosemary Zuna and William V. Stoecker and Jason Hagerty},
title={Nuclei Segmentation using a Level Set Active Contour Method and Spatial Fuzzy C-means Clustering},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={195-202},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006136201950202},
isbn={978-989-758-225-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Nuclei Segmentation using a Level Set Active Contour Method and Spatial Fuzzy C-means Clustering
SN - 978-989-758-225-7
AU - Edulapuram R.
AU - Stanley R.
AU - Long R.
AU - Antani S.
AU - Thoma G.
AU - Zuna R.
AU - Stoecker W.
AU - Hagerty J.
PY - 2017
SP - 195
EP - 202
DO - 10.5220/0006136201950202