• Laser & Optoelectronics Progress
  • Vol. 58, Issue 8, 0817001 (2021)
Zhaoxu Li1, Tao Song2, Mengfei Ge1, Jiaxin Liu1, Hongwei Wang1、3, and Jia Wang2、*
Author Affiliations
  • 1School of Electrical Engineering, Xinjiang University, Urumqi, Xinjiang 830000, China
  • 2School of Basic Medicine Science, Dalian Medical University, Dalian, Liaoning 110041, China
  • 3School of Control Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116023, China
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    DOI: 10.3788/LOP202158.0817001 Cite this Article Set citation alerts
    Zhaoxu Li, Tao Song, Mengfei Ge, Jiaxin Liu, Hongwei Wang, Jia Wang. Breast Cancer Classification from Histopathological Images Based on Improved Inception Model[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0817001 Copy Citation Text show less
    Histopathological patches after image preprocessing
    Fig. 1. Histopathological patches after image preprocessing
    Architecture of convolutional neural network
    Fig. 2. Architecture of convolutional neural network
    Architecture of model and internal structure. (a) Architecture of improved model; (b) architecture of Pre-treatment module; (c) architecture of Inception module
    Fig. 3. Architecture of model and internal structure. (a) Architecture of improved model; (b) architecture of Pre-treatment module; (c) architecture of Inception module
    Overall strategy of experiment. (a) Process of training; (b) process of testing
    Fig. 4. Overall strategy of experiment. (a) Process of training; (b) process of testing
    Loss change during training iterative process
    Fig. 5. Loss change during training iterative process
    Picture sizeConvergence times /min
    299 pixel×299 pixel967
    512 pixel×512 pixel713
    700 pixel×700 pixel1219
    Table 1. Convergence time of model under different the image sizes
    learning_ratePrecision /%Recall /%
    0.186.375.1
    0.0191.789.4
    0.00196.193.1
    Table 2. Test results corresponding different learning_rate
    ModelConvergence times/min
    LeNet1346
    AlexNet1120
    VGG-161219
    GoogleNet927
    Proposed model713
    Table 3. Convergence time of different models
    ModelSensitivity /%Specificity /%Accuracy /%
    LeNet76.3277.8374.57
    AlexNet89.2391.2290.10
    VGG-1693.1596.1793.21
    GoogleNet96.193.195.19
    Proposed model96.1398.4796.12
    Table 4. Performance of the different models
    Zhaoxu Li, Tao Song, Mengfei Ge, Jiaxin Liu, Hongwei Wang, Jia Wang. Breast Cancer Classification from Histopathological Images Based on Improved Inception Model[J]. Laser & Optoelectronics Progress, 2021, 58(8): 0817001
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