Gastric Carcinoma Classification Based on Convolutional Neural Network and Micro-Hyperspectral Imaging

Jian Du; Bingliang Hu; Zhoufeng Zhang

doi:10.3788/AOS201838.0617001

Acta Optica Sinica, Volume. 38, Issue 6, 0617001(2018)

Gastric Carcinoma Classification Based on Convolutional Neural Network and Micro-Hyperspectral Imaging

Jian Du^1,2, Bingliang Hu^1、*, and Zhoufeng Zhang¹

¹ Key Laboratory of Spectral Imaging Technology of Chinese Academy of Sciences, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi 710119, China

² University of Chinese Academy of Sciences, Beijing 100049, China

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Figures & Tables(9)

Fig. 1. Illustration of local connection

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Fig. 2. Flow chart of CNN modeling towards medical micro-hyperspectral data

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Fig. 3. Micro-hyperspectral imaging system

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Fig. 4. (a) Micro-hyperspectral data cube of gastric tissue; (b) schematic of pixel point spectrum curve extraction

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Fig. 5. Average spectra of gastric cancer tissue and normal tissue

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Fig. 6. Variations of training loss and classification accuracy with the number of iterations

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Table 1. Statistics of training and test sets of samples
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Table 1. Statistics of training and test sets of samples
Sample Training set Test set Sum
Gastric cancer tissue 800 140 940
Normal tissue 800 140 940
Sum 1600 280 1880

Table 2. Specific parameters of CNN classification model of gastric carcinoma slices
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Table 2. Specific parameters of CNN classification model of gastric carcinoma slices
No. I1 C2 P3 C4 P5 F6 O7 Accuracy /%
N(×S) CNN-1 200 8×5 1×2 16×5 1×2 100 2 92.50
CNN-2 200 10×7 1×4 - 100 2 93.75
CNN-3 200 22×17 1×4 - 100 2 96.53

Table 3. Classification results obtained by three kinds of models
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Table 3. Classification results obtained by three kinds of models
Model Accuracy /% Sensitivity /% Specificity /%
NN 89.14 91.43 88.57
RBF-SVM 92.62 91.43 93.57
Our CNN 96.53 94.29 97.14

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Jian Du, Bingliang Hu, Zhoufeng Zhang. Gastric Carcinoma Classification Based on Convolutional Neural Network and Micro-Hyperspectral Imaging[J]. Acta Optica Sinica, 2018, 38(6): 0617001

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