Table 1 CNN-Res detailed architecture

Input

(\(160\times 160\))

(\(160\times 160\times 1\))

Transition Block 1

\(\left[\begin{array}{c}Conv \left(3\times 3\right).BN.Relu.S=1\\ \mathrm{max}pooling \left(2\times 2\right).S=2\end{array}\right]\)

(\(80\times 80\times 32\))

Residual Block 1

\(\left[\begin{array}{c}BN.ReLU.Conv\left(1\times 1\right).S=1\\ BN.ReLU.Conv\left(3\times 3.S=1\right)\end{array}\right]\)

(\(80\times 80\times 64\))

Transition Block 2

\(\left[\begin{array}{c}Conv \left(3\times 3\right).BN.Relu.S=1\\ \mathrm{max}pooling \left(2\times 2\right).S=2\end{array}\right]\)

(\(40\times 40\times 64\))

Residual Block 2

\(\left[\begin{array}{c}BN.ReLU.Conv\left(1\times 1\right).S=1\\ BN.ReLU.Conv\left(3\times 3.S=1\right)\end{array}\right]\)

(\(40\times 40\times 128\))

Transition Block 3

\(\left[\begin{array}{c}Conv \left(3\times 3\right).BN.Relu.S=1\\ \mathrm{max}pooling \left(2\times 2\right).S=2\end{array}\right]\)

(\(20\times 20\times 128\))

Residual Block 3

\(\left[\begin{array}{c}BN.ReLU.Conv\left(1\times 1\right).S=1\\ BN.ReLU.Conv\left(3\times 3.S=1\right)\end{array}\right]\)

(\(20\times 20\times 256\))

Transition Block 4

\(\left[\begin{array}{c}Conv \left(3\times 3\right).BN.Relu.S=1\\ \mathrm{max}pooling \left(2\times 2\right).S=2\end{array}\right]\)

(\(10\times 10\times 256\))

Residual Block 4

\(\left[\begin{array}{c}BN.ReLU.Conv\left(1\times 1\right).S=1\\ BN.ReLU.Conv\left(3\times 3.S=1\right)\end{array}\right]\)

(\(10\times 10\times 512\))

Bottleneck

\(\left[\begin{array}{c}Conv \left(3\times 3\right).BN.Relu.S=1\\ \mathrm{max}pooling \left(2\times 2\right).S=2\end{array}\right]\)

(\(5\times 5\times 512\))

\(\left[\begin{array}{c}BN.ReLU.Conv\left(1\times 1\right).S=1\\ BN.ReLU.Conv\left(3\times 3.S=1\right)\end{array}\right]\)

(\(5\times 5\times 1024\))

\(\left[BN.ReLU.Conv\left(1\times 1\right).S=1\right]\)

(\(5\times 5\times 64\))

Upsampling block

Upsampling 1

\(\left[\mathrm{Upsampling}\left(2\times 2\right)\right]\)

(\(10\times 10\times 64\))

Concatenate

\(\left[\mathrm{Transition Block }4.\mathrm{Upsampling}1\right]\)

(\(10\times 10\times 320\))

Conv 1

\(Conv\left(3\times 3\right).ReLU.S=1\)

(\(10\times 10\times 256\))

Upsampling block

Upsampling 2

\(\mathrm{Upsampling}\left(2\times 2\right)\)

(\(20\times 20\times 256\))

Concatenate

\(\left[\mathrm{Transition Block }3.\mathrm{Upsampling}2\right]\)

(\(20\times 20\times 384\))

Conv 2

\(Conv\left(3\times 3\right).ReLU.S=1\)

(\(20\times 20\times 128\))

Upsampling block

Upsampling 3

\(\mathrm{Upsampling}\left(2\times 2\right)\)

(\(40\times 40\times 128\))

Concatenate

\(\left[\mathrm{Transition Block }2.\mathrm{Upsampling}3\right]\)

(\(40\times 40\times 192\))

Conv 3

\(Conv\left(3\times 3\right).ReLU.S=1\)

(\(40\times 40\times 64\))

Upsampling block

Upsampling 4

\(\mathrm{Upsampling}\left(2\times 2\right)\)

(\(80\times 80\times 64\))

Concatenate

\(\left[\mathrm{Transition Block }1.\mathrm{Upsampling}4\right]\)

(\(80\times 80\times 96\))

Conv 4

\(Conv\left(3\times 3\right).ReLU.S=1\)

(\(80\times 80\times 64\))

Conv 5

\(Conv\left(3\times 3\right).ReLU.S=1\)

(\(80\times 80\times 32\))

Upsampling 5

\(\mathrm{Upsampling}\left(2\times 2\right)\)

(\(160\times 160\times 32\))

Conv5

\(Conv\left(1\times 1\right).Sigmoid.S=1\)

(\(160\times 160\times 1\))

Output

\(Segmentation map\)

(\(160\times 160\times 1\))