Journal
OPTIK
Volume 127, Issue 24, Pages 11901-11910Publisher
ELSEVIER GMBH, URBAN & FISCHER VERLAG
DOI: 10.1016/j.ijleo.2016.09.046
Keywords
Automatic cytometry; Segmentation; Detection; Leukocytes; Color decomposition
Categories
Funding
- National Natural Science Foundation of China [61403257, 61571274]
- Shenzhen Fundamental Research fund [JCYJ20150324140036868]
- Fundamental Research Funds of Shandong University [2015JC038]
- Science and Technology Development Plans of Jinan City
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The automatic detection of leukocytes is essential for cytometry and type recognition. Although this problem has been given much attention, the accuracy and speed of leukocyte detection still needs to be improved to meet the requirements of practical applications. This paper presents an effective method of detecting leukocytes. In this method, color decomposition and adaptive binarization are firstly used to detect the background and red blood cells, then the leukocytes can be roughly detected. After denoising, border refinement is applied to modify the false border of the roughly detected leukocytes, and a novel nucleus enhancing method is used to identify nucleus, which can be used to detect false leukocytes. The proposed leukocyte detection method is evaluated using the blood cell image data set. The experimental results demonstrate that the proposed method outperforms two traditional methods, namely the region growing and snake methods, with higher accuracy and shorter computing time. (C) 2016 Elsevier GmbH. All rights reserved.
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