RESUMEN
A new leukocyte classification method for recognition of five types of human peripheral blood smear based on mean-shift clustering is proposed. The key idea of the proposed method is to extract the texture features of leukocytes in a visual manner which can benefit from human eyes. Firstly, some feature points are extracted in a gray leukocyte image by mean-shift. Secondly, these feature points are used as seeds of the region growing to expand feature regions which can express texture in visual mode to a certain extent. Finally, a parameter vector of these regions is extracted as the texture feature. Combing the vector with the geometric features of the leukocyte, the five typical classes of leukocytes can be recognized successfully using artificial neural network (ANN). A total number of 1 310 leukocyte images have been tested and the accurate rate of recognition for neutrophil, eosinophil, basophil, lymphocyte and monocyte are 95.4%, 93.8%, 100%, 93.1% and 92.4%, respectively, which shows the feasibility and high robustness of the proposed method.
RESUMEN
The combination of nanotechnology and molecular imprinting technique, including their application research in biomedical domain, provides a new solution to the problem of the substitutes for antibodies, enzymes, and other native biological structures as well as cell bracket materials. Nanocavity biomaterials with recognition specificity imprinted by using proteins as templates have numerous applications in biotechnology, medicine and so on. This review presents the aspects of molecular imprinting nanostructure involved in the biomacromolecules imprinting, and it explores the precent developments and achievements of nanomaterials for molecular imprinting technology.