White Blood Cells Identification and Counting from Microscopic Blood Images

The counting and analysis of blood cells allows the evaluation and diagnosis of a vast number of diseases. In particular, the analysis of white blood cells (WBCs) is a topic of great interest to hematologists. Nowadays the morphological analysis of blood cells is performed manually by skilled operators. This involves numerous drawbacks, such as slowness of the analysis and a nonstandard accuracy, dependent on the operator skills. In literature there are only few examples of automated systems in order to analyze the white blood cells, most of which only partial. This paper presents a complete and fully automatic method for white blood cells identification from microscopic images. The proposed method firstly individuates white blood cells from which, subsequently, nucleus and cytoplasm are extracted. The whole work has been developed using MATLAB environment, in particular the Image Processing Toolbox. Keywords—Automatic detection, Biomedical image processing, Segmentation, White blood cell analysis.

[1]  F. Scotti,et al.  Robust Segmentation and Measurements Techniques of White Cells in Blood Microscope Images , 2006, 2006 IEEE Instrumentation and Measurement Technology Conference Proceedings.

[2]  Joakim Lindblad,et al.  Development of Algorithms for Digital Image Cytometry , 2002 .

[3]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[4]  I. Cseke,et al.  A fast segmentation scheme for white blood cell images , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

[5]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .