Abstract

In this paper we overview an automated method for the analysis of clinical parameters of human red blood cells (RBCs). The digital holograms of mature RBCs are recorded by CCD camera with off-axis interferometry setup and the quantitative phase images of RBCs are formed by a numerical reconstruction technique. For automated investigation of the 3D morphology and mean corpuscular hemoglobin of RBCs, the unnecessary background in the RBCs phase images are removed by marker-controlled watershed segmentation algorithm. Then, characteristic properties of each RBC such as projected cell surface, average phase, mean corpuscular hemoglobin (MCH) and (MCH) surface density is quantitatively measured. Finally, the equality of covariance matrixes and mean vectors of these features for different kinds of RBCs are experimentally analyzed using statistical test scheme. Results show that these characteristic parameters of RBCs can be used as feature pattern to discriminate between RBC populations that differ in shape and hemoglobin content.

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