Title :
Robust recognition of white blood cell images
Author :
Kovalev, Vassili A. ; Grigoriev, Andrei Y. ; Ahn, Hyo-Sok
Author_Institution :
Inst. of Math., Acad. of Sci., Gomel, Byelorussia
Abstract :
The objective of this work is to investigate the white blood cell (WBC) image recognition problem at all stages. A robust and effective method for automatic WBC differentiation, based on both statistical pattern recognition and neural net approaches, is presented. We demonstrate well-evaluated results ranging from image scene segmentation techniques to recognition details. Recognition accuracy on the test set of 662 images of five WBC types obtained by different imaging systems from 22 bloodstains is not less than 98%
Keywords :
biological techniques; blood; cellular biophysics; feature extraction; image recognition; image segmentation; medical image processing; neural nets; object recognition; statistical analysis; automatic differentiation; bloodstains; disease diagnosis; image scene segmentation; neural net; robust recognition; statistical pattern recognition; white blood cell images; Counting circuits; Image recognition; Image segmentation; Layout; Microscopy; Optical imaging; Optical scattering; Pattern recognition; Robustness; White blood cells;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.547448
