Acute Lymphoblastic Leukemia Classification Method Based on Attention Residual Network
Yufei Shao, Weihe Yu · 2023
Aiming at the problems of error-prone and time-consuming classification of Acute lymphoblastic leukemia (ALL) blood cell microscopic images in medicine, this paper proposes a method based on the attention mechanism residual convolutional neural network model to obtain the information in medical images. Complicated pathological information. This method first preprocesses the sample data, cleans out the training set and verification set that meet the requirements, and also uses the threshold segmentation method to extract the target area of the training sample, and then inputs the preprocessed data into the network. In the model, it is trained, and finally the verification set is input into the model for verification. The experimental results show that this classification method can effectively classify whether ALL blood cell microscopic images are diseased.