AUTOMATED DIFFERENTIAL BLOOD COUNT USING IMAGE QUANTIZATION
Keywords:
Blood Smear, White Blood Cells, Red Blood Cells, Platelets, hematology, Quantization, digital image processingAbstract
Objective: The objective of this research is to automate the calculation of differential blood count in blood smear photomicrographs
using image quantization.
Material and Methods: A series of image processing steps were used for the detection of White Blood Cells (WBCs),
Red Blood Cells (RBCs) and platelets as: image acquisition, separating the channels of RGB and applying wiener filter
on each channel for smoothing the image. The purpose is to enhance the visual interpretation of the image, recombining
the channels and applying the quantization over the wiener output.
Results: The accuracy of this technique is very close to that of the hematologists’ manual calculation. It was 85% for
Red blood cells and 98% for White blood cells.
Conclusion: This proposed technique gives precise results under varied luminance conditions such as darkness,
brightness and low contrast images, it gives reliable results for all the images in the image sets having different quality
of images
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