Automatic recognition of five types of white blood cells in peripheral blood
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part II
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The differential counting of white blood cells provides invaluable information to hematologist for diagnosis and treatment of many diseases. Manually counting of white blood cells is a tiresome, time-consuming and susceptible to error procedure. Due to the tedious nature of this process, an automatic system is preferable. In this automatic process, Segmentation of white blood cells is one of the most important stages. The nucleus of white blood cells has the most information about the type of white blood cells, thus an exact segmentation seems to be helpful for other stages of automatic recognition of white blood cells. In this paper, we introduced a novel method based on orthogonality theory and Gram-Schmidt process for segmenting the nuclei of white blood cells. For evaluation of results, we compared our proposed method with a hematologist manual segmentation. Results show robustness of this technique for segmentation of nuclei, while this method is very simple to implement.