|本期目录/Table of Contents|

[1]庄杨凯,周平.基于多证据的血液白细胞自动分类[J].浙江理工大学学报,2013,30(03):367-371.
 ZHUANG Yangkai,ZHOU Ping.Automatic Classification of Leukocytes in Blood Based on Multievidence[J].Journal of Zhejiang Sci-Tech University,2013,30(03):367-371.
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基于多证据的血液白细胞自动分类()
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浙江理工大学学报[ISSN:1673-3851/CN:33-1338/TS]

卷:
第30卷
期数:
2013年03期
页码:
367-371
栏目:
(自科)生物与生命科学
出版日期:
2013-05-10

文章信息/Info

Title:
Automatic Classification of Leukocytes in Blood Based on Multievidence
文章编号:
1673-3851 (2013) 03-0367-05
作者:
庄杨凯 周平
江理工大学信息学院, 杭州 310018
Author(s):
ZHUANG Yangkai ZHOU Ping
School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China
关键词:
白细胞分类 欧氏距离变换 不变矩 形态学特征 纹理特征 支持矢量机
分类号:
TP391.4
文献标志码:
A
摘要:
对白细胞分类方法提出了一种基于形状特征学习的分类算法。该算法首先从细胞核中提取基于欧氏距离变换的不变矩特征和形态学特征;然后,所提取的特征可以实现对单核细胞、淋巴细胞、嗜碱性粒细胞的分类;最后,提取灰度共生矩阵作为纹理特征,通过支持矢量机实现对剩余白细胞类别的分类。实验结果表明,该方法具有很好的分类准确率及较短的处理时间。

参考文献/References:

[1]Rezatofighi S H, Soltanian Zadeh H. Automatic recognition of five types of white blood cells in peripheral blood[J]. Computerized Medical Imaging and Graphics, 2011, 35: 333-343.
[2]Guo N, Zeng L, Wu Q. A method based on multispectral imaging technique for white blood cell segmentation[J]. Computers in Biology and Medicine, 2006, 37: 70-76.
[3] Ghosh M, Das D, Chakraborty C, et al. Automated leukocyte recognition using fuzzy divergence[J]. Micron, 2010, 41: 840-846.
[4] Ko B C, Gim J W, Nam J Y. Automatic white blood cell segmentation using stepwise merging rules and gradient vector flow snake[J]. Micron, 2011, 42: 695-705.
[5] Li  K, Lu Z, Liu W, et al. Cytoplasm and nucleus segmentation in cervical smear images using Radiating GVF Snake[J]. Pattern Recognition, 2012, 45(4): 1255-1264.
[6] Pan C, Park D S, Yoon S, et al. Leukocyte image segmentation using simulated visual attention[J]. Expert Systems with Applications, 2012, 39(8): 7479-7494.
[7] Huang D C, Huang K D, Chan Y K. A computer assisted method for leukocyte nucleus segmentation and recognition in blood smear images[J]. The Journal of Systems and Software, 2012, 85: 2104-2118.
[8] Ko B C, Gim J W, Nam J Y. Cell image classification based on ensemble features and random forest[J]. Electronics Letters, 2011, 47(11): 638-639.
[9] Sabino D M U, Costa L F, Rizzatti E G, et al. A texture approach to leukocyte recognition[J]. RealTime Imaging, 2004, 10: 205-216.
[10] TheeraUmpon N. White blood cell segmentation and classification in microscopic bone marrow images[J]. Fuzzy Systems and Knowledge Discovery, Lecture Notes in Computer Science, 2005, 3614: 787-796.
[11] RamirezCortes J M, GomezGil P, AlarconAquino V, et al. Neural networks and svmbased classification of leukocytes using the morphological pattern spectrum[J]. Soft Computing for Recognition Based on Biometrics, 2010, 312: 19-35.
[12] Jin L, Tianxu Z. Fast algorithm for generation of moment invariants[J]. Pattern Recognition, 2004, 37: 1745-1756.
[13] Honeycutt C E, Plotnick R. Image analysis techniques and graylevel cooccurrence matrices (GLCM) for calculating bioturbation indices and characterizing biogenic sedimentary structures[J]. Computers & Geosciences, 2008, 34: 1461-1472.
[14] Nie F, Gao C, Guo Y, et al. Twodimensional minimum local crossentropy thresholding based on cooccurrence matrix[J]. Computers and Electrical Engineering, 2011, 37: 757-767.

备注/Memo

备注/Memo:
收稿日期: 2012-11-15
作者简介: 庄杨凯(1988-),男,浙江奉化人,硕士研究生,主要从事图像处理方面的研究。
通信作者: 周平,电子邮箱:zp@zstu.edu.cn
更新日期/Last Update: