CNN-based leukocyte detection for microscopy imaging at 10x magnification objective lens

Examination of peripheral blood smears by light microscopy helps to provide valuable information for disease diagnosis, but remains one of the major labor-intensive procedures in hematology laboratory. As a key part of white blood cell morphology examination, leukocyte detection at 10× magnification objective lens is considered as small object detection problem in this paper. After establishing leukocyte dataset at 10× magnification objective lens, we design a classification-based two-stage approach to this challenging problem. Stage one generates proposals by pixellevel ANN pipeline based on the color and size of leukocyte. Stage two is responsible for proposal classification task by CNN architecture. Extensive experiments are carried out to prove its effectiveness for peripheral blood samples. Experimental results demonstrate that the proposed classification-based approach, obtains a desired precision of 94.69%, recall of 95.73%, accuracy of 90.85% and F_β of 0.96. The data is available at https://doi.org/10.6084/m9.figshare.9037370.v1.