Scholarly Research Excellence
%0 Journal Article
%A Lorenzo Putzu and  Cecilia Di Ruberto
%D 2013 
%J  International Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 73, 2013
%T White Blood Cells Identification and Counting from Microscopic Blood Image
%U http://waset.org/publications/189
%V 73
%X 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.
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