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. Author manuscript; available in PMC: 2018 Jan 1.
Published in final edited form as: J Xray Sci Technol. 2017;25(5):751–763. doi: 10.3233/XST-16226

Table 2.

Details of the structures of the each layer in the deep learning network

1st layer 2nd layer 3rd layer 4th layer 5th layer 6th layer 7th layer 8th layer
Layer type Convolution Max-pooling Convolution Max-pooling Convolution Max-pooling Hidden Logistic regression
Number of feature maps 20 N/A 10 N/A 5 N/A N/A N/A
Filter size 9×9 N/A 5×5 N/A 5×5 N/A N/A N/A
Input size 64×64 20×56×56 20×28×28 10×24×24 10×12×12 5×8×8 5×4×4 50
Output size 20×56×56 20×28×28 10×24×24 10×12×12 5×8×8 5×4×4 50 2