An Artificial Intelligence-Assisted Diagnostic Classification Research on Blood Cell Microscopic
Image of Acute Lymphoblastic Leukemia Based on VGG16 Model
ZHANG Haitao1, LIU Jingxin2, ZHAO Xiaoqing1, HU Xiaohan3, LI Huiying1
1. School of Computer Science and Technology, Jilin University, Changchun Jilin 130012, China;
2. Department of Radiology, China-Japan Union Hospital, Jilin University, Changchun Jilin 130033, China;
3. Department of Radiology, The First Hospital, Jilin University, Changchun Jilin 130021, China
Abstract:Aiming at the problem of accurate classification and time consuming in clinical medicine microscopic images of
acute lymphoblastic leukemia (ALL), this paper proposed a method based on deep learning VGG16 convolutional neural
network model to obtain pathological information at high latitudes in medical images. In the paper, we firstly preprocessed
the sample, cleaned out the training set and verification set that met the requirements, and also used the super-pixel method to
extract the target area of the training sample. Then we trained VGG16 network by inputting the preprocessed data, and finally
the validation set was entered into the model for verification. The experimental result showed that the classification method
could effectively complete the classification of ALL blood cell microscopic images.
张海涛1,刘景鑫2,赵晓晴1,胡笑含3,李慧盈1. 基于VGG16的急性淋巴细胞白血病血液细胞显微图像人工智能辅助诊断分类研究[J]. 中国医疗设备, 2019, 34(7): 1-4.
ZHANG Haitao1, LIU Jingxin2, ZHAO Xiaoqing1, HU Xiaohan3, LI Huiying1. An Artificial Intelligence-Assisted Diagnostic Classification Research on Blood Cell Microscopic
Image of Acute Lymphoblastic Leukemia Based on VGG16 Model. China Medical Devices, 2019, 34(7): 1-4.