Automatic cytoplasm and nuclei segmentation for color cervical smear image using an efficient gap-search MRF
Automatic cytoplasm and nuclei segmentation for color cervical smear image using an efficient gap-search MRF
复制标题
使用高效间隙搜索 MRF 对彩色宫颈涂片图像进行自动细胞质和细胞核分割
DOI:
10.1016/j.compbiomed.2016.01.025
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发表时间:
2016-04
影响因子:
7.7
通讯作者:
Zhu, Chengzhang
中科院分区:
文献类型:
--
作者:
Zhu, En;Wu, Chengkun;Wang, Siqi;Zhu, Chengzhang
Accurate and effective cervical smear image segmentation is required for automated cervical cell analysis systems. Thus, we proposed a novel superpixel-based Markov random field (MRF) segmentation framework to acquire the nucleus, cytoplasm and image background of cell images. We seek to classify color non-overlapping superpixel-patches on one image for image segmentation. This model describes the whole image as an undirected probabilistic graphical model and was developed using an automatic label-map mechanism for determining nuclear, cytoplasmic and background regions. A gap-search algorithm was designed to enhance the model efficiency. Data show that the algorithms of our framework provide better accuracy for both real-world and the public Herlev datasets. Furthermore, the proposed gap-search algorithm of this model is much more faster than pixel-based and superpixel-based algorithms.
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DOI:
10.1109/wccct.2014.89
发表时间:
2014-02
期刊:
2014 World Congress on Computing and Communication Technologies
影响因子:
--
作者:
G. Lakshmi;K. Krishnaveni
通讯作者:
G. Lakshmi;K. Krishnaveni
DOI:
10.1109/iccv.2013.359
发表时间:
2013-12
期刊:
2013 IEEE International Conference on Computer Vision
影响因子:
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作者:
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Xiangfei Kong;Kuan Li;Qingxiong Yang;Wenyin Liu;Ming-Hsuan Yang
DOI:
10.1016/j.procs.2015.08.228
发表时间:
2015
期刊:
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影响因子:
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作者:
S. N. Sulaiman;N. Isa;N. Othman;F. Ahmad
通讯作者:
S. N. Sulaiman;N. Isa;N. Othman;F. Ahmad
DOI:
10.1049/ip-vis:19981690
发表时间:
1998-02
期刊:
--
影响因子:
--
作者:
Haisang Wu
通讯作者:
Haisang Wu
DOI:
--
发表时间:
--
期刊:
--
影响因子:
--
作者:
Ling Zhang;Hui Kong;Ti-Hsuan Chien;Chin;Shaoxiong Liu;Zhi Chen;Tianfu Wang;Siping Chen
通讯作者:
Ling Zhang;Hui Kong;Ti-Hsuan Chien;Chin;Shaoxiong Liu;Zhi Chen;Tianfu Wang;Siping Chen