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Table 2 The structure of the 3D dense connection DCNN

From: Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method

Layer name

Structure

 

7×7×7 conv

 

3×3×3 max pool

Dense block

\(\begin {bmatrix} 1 \times 1 \times 1 \text { conv}\\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×6

Transition

1×1×1 conv2×2×2 avg pool

Dense block

\(\begin {bmatrix} 1 \times 1 \times 1 \text { conv} \\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×12

Transition

1×1×1 conv2×2×2 avg pool

Dense block

\(\begin {bmatrix} 1 \times 1 \times 1 \text { conv} \\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×24

Transition

1×1×1 conv2×2×2 avg pool

Dense block

\(\begin {bmatrix} 1 \times 1 \times 1 \text { conv} \\ 3 \times 3 \times 3 \text { conv} \end {bmatrix}\) ×16

 

7×7×7 avg pool1000-d FCsoftmax

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BMC Medical Imaging

ISSN: 1471-2342

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