Table 1 Network architecture of ResNet34 and 3D Res18

Conv1

112 × 112

[2D conv7 × 7 64]

Conv1

7 × 7 × 128

{3Dconv3 × 3 × 3128

3Dconv3 × 3 × 3128} × 2

pool

56 × 56

[max pool 3 × 3]

Conv2

7 × 7 × 256

{3Dconv3 × 3 × 3256

3Dconv3 × 3 × 3256} × 2

Layer1

56 × 56

{2D conv3 × 3 64

2D conv3 × 3 64} × 3

Conv3

7 × 7 × 512

{3Dconv3 × 3 × 3512

3Dconv3 × 3 × 3512} × 2

Layer2

28 × 28

{2D conv3 × 3128

2D conv3 × 3128} × 4

Pooling

1 × 1 × 512

[Avgpool3D 1 × 7 × 7]

Layer3

14 × 14

{2D conv3 × 3256

2D conv3 × 3256} × 6

Dropout

1 × 8192

Dropout (p = 0.5)

Layer4

7 × 7

{2D conv3 × 3512

2D conv3 × 3512} × 3

–

1 × classes

FC, softmax