In order to explore the cell composition and its metabolism, it is important to let computer recognize
the cells and get the counts of different cells for a sample. This paper proposes an L-shaped envelop function and
the related fuzzy clustering method as a way to identify the megakaryocyte and the red cell from the sliced marrow
image. This method is useful when the staining is insufficient and the color cannot be used as the identifying
factor. This method uses the experimental histogram data to fit the L-shaped function and then use it as the
envelop for the match test. The fuzzy c-means (FCM) performance index is used to test the adjacent area and
get the minimum and finally secure the identification. The new method is not limited to megakaryocyte or red
cell and can be used for general purposes of cell recognition. Tests show that this envelop function can ensure
the recognition rate with different staining batches and can reach satisfied counting under similar illumination
condition.
YU Ye-hua1 (俞夜花), ZHENG Xi-tao2 (郑西涛), ZHANG Yong-wei2 (张永伟),YANG Kun2 (杨 堃), ZHANG Jing1 (章菁), SHI Jun1* (石军)
. Recognition of Red Cell and Megakaryocyte Based L-Shaped Envelope Function[J]. Journal of Shanghai Jiaotong University(Science), 2012
, 17(6)
: 755
-760
.
DOI: 10.1007/s12204-012-1359-9
[1] Zheng X T, Shi J, Yu Y H, et al. A new method for automatic counting of marrow cells [C]//Proceeding of the 4th International Conference on Biomedical Engineering and Informatics. [s.l.]: IEEE, 2011: 44-48.
[2] Zheng X T, Shi J, Yu Y H, et al. Analysis of leukemia development based on marrow cell images [C]//Proceeding of the 4th International Congress on Image and Signal Processing. [s.l.]: IEEE, 2011: 95-99.
[3] Ababneh S Y, Prescott J W, Gurcan M N. Automatic graph-cut based segmentation of bones from knee magnetic resonance images for osteoarthritis research [J]. Medical Image Analysis, 2011, 15(4): 438-448.
[4] Brown E S, Chan T F, Bresson X. Completely convex formulation of the Chan-vese image segmentation model [J]. International Journal of Computer Vision, 2012, 98: 103-121.
[5] Cruz-Mota J, Bogdanova I, Paquier B, et al. Scale invariant feature transform on the sphere: Theory and applications [J]. International Journal of Computer Vision, 2012, 98: 217-241.
[6] Wang E Y, Gou Z P, Miao A M, et al. Recognition of blood cell images based on color fuzzy clustering [J]. Fuzzy Information and Engineering, 2009, 62: 69-75.
[7] Theera-Umpon N. Patch-based white blood cell nucleus segmentation using fuzzy clustering [J]. Transactions on Electrical Engineering, Electronics, and Communications, 2005, 3: 15-19.
[8] Ai Da-ping, Yin Xiao-hong, Liu Bo-qiang, et al. The algorithm of marrow cell identification and classification [J]. Chinese Journal of Biomedical Engineering, 2009, 28(4): 549-553 (in Chinese).
[9] Zheng X T, Zhang Y W. A fish population counting method using fuzzy artificial neural network [C]//The 2010 International Conference on Progress in Informatics and Computing Conference. [s.l.]: IEEE, 2010: 225-228.
