Complete three‐phase detection framework for identifying abnormal cervical cells-Reference-Cited by-同舟云学术

Complete three‐phase detection framework for identifying abnormal cervical cells

Published:2017-02-16 Issue:4 Volume:11 Page:258-265
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Zhao Lili¹,Li Kuan²,Yin Jianping³,Liu Qiang¹,Wang Siqi¹

Affiliation:

1. College of Computer, National University of Defense TechnologyChangshaPeople's Republic of China

2. Institute of Software, College of Computer, National University of Defense TechnologyChangshaPeople's Republic of China

3. State Key Laboratory of High Performance ComputingNational University of Defense TechnologyChangshaPeople's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2016.0788

Reference34 articles.

1. Cytoplasm and nucleus segmentation in cervical smear images using Radiating GVF Snake

2. Segmentation of cervical cell nuclei in high-resolution microscopic images: A new algorithm and a web-based software framework

3. Segmentation of cytoplasm and nuclei of abnormal cells in cervical cytology using global and local graph cuts

4. 2014 Engineering in Medicine and Biology Society (EMBC) 36th Annual Int. Conf. of the IEEE Y. Song L. Zhang S. Chen A deep learning based framework for accurate segmentation of cervical cytoplasm and nuclei 2903 2906

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