title: An on-chip instrument for white blood cells classification based on a lens-less shadow imaging technique.
abstract: Routine blood tests provide important basic information for disease diagnoses. The proportions of three subtypes of white blood cells (WBCs), which are neutrophils, monocytes, lymphocytes, is key information for disease diagnosis. However, current instruments for routine blood tests, such as blood cell analyzers, flow cytometers, and optical microscopes, are cumbersome, time consuming and expensive. To make a smaller, automatic low-cost blood cell analyzer, much research has focused on a technique called lens-less shadow imaging, which can obtain microscopic images of cells in a lens-less system. Nevertheless, the efficiency of this imaging system is not satisfactory because of two problems: low resolution and imaging diffraction phenomena. In this paper, a novel method of classifying cells with the shadow imaging technique was proposed. It could be used for the classification of the three subtypes of WBCs, and the correlation of the results of classification between the proposed system and the reference system (BC-5180, Mindray) was 0.93. However, the instrument was only 10 × 10 × 10 cm, and the cost was less than $100. Depending on the lens-free shadow imaging technology, the main hardware could be integrated on a chip scale and could be called an on-chip instrument.
authors.affiliation: School of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.|School of Electrical and Electronic Engineering, Baoji University of Arts and Sciences, Baoji, Shaanxi Province, China.
authors.forename: Yuan
authors.identifier: http://orcid.org/0000-0002-5138-3895
authors.initials: Y
authors.lastname: Fang
authors.affiliation: School of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.
authors.forename: Ningmei
authors.identifier: http://orcid.org/0000-0002-4219-8364
authors.initials: N
authors.lastname: Yu
authors.affiliation: School of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.
authors.forename: Runlong
authors.initials: R
authors.lastname: Wang
authors.affiliation: School of Automation and Information Engineering, Xi'an University and Technology, Xi'an, Shaanxi Province, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Su
mesh_terms: D000465:Algorithms; D015374:Biosensing Techniques / Q000191:economics / Q000295:instrumentation* / Q000379:methods; D003362:Cost-Benefit Analysis; D006801:Humans; D056656:Lab-On-A-Chip Devices; D007958:Leukocyte Count; D007962:Leukocytes / Q000145:classification / Q000166:cytology*; D008670:Metals / Q000737:chemistry; D061848:Optical Imaging / Q000191:economics / Q000295:instrumentation* / Q000379:methods; D010087:Oxides / Q000737:chemistry; D015203:Reproducibility of Results; D012666:Semiconductors
chemical_list: D008670:Metals; D010087:Oxides