The invention relates to a medical
image processing and recognition technology, in particular to a
blood cell automatic detection method based on a grading strategy, which comprises the following steps: acquiring a
blood cell image set with a
label, performing data enhancement on the
data set to obtain a first training
data set, and selecting a
minority class of samples in the first training
data set as a second training data set; training a secondary classification network by using the second training data set; constructing an improved YOLOv8 target detection
algorithm model, and if the category output by a detection head in the YOLOv8 target detection
algorithm model is not a minority category, directly outputting a detection result; and if the category of the single
cell image output by the detection head is a minority category, inputting the single
cell image into a pre-trained secondary classification network, and obtaining a final category probability by combining the confidence of the secondary classification network with an improved YOLOv8 target detection
algorithm model. The method can improve the detection accuracy and the
detection rate, and is suitable for the scene of
peripheral blood cell detection.