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Table 2 Selected hyper parameters for training and inference

From: Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol

Parameter

Training

Inference

Window size

320, 320, 320

400, 400, 400

Activation function

PRelu

 

Loss type

DicePlusXEnt

 

Normalization

Histogram

Histogram

Window sampling

Weighted

Weighted

Volume padding

24, 24, 24

0, 0, 0

Learning rate

0.0001

 

Random flipping axes

(0, 2)

 

Elastic transformation

True

 

Rotation angle

(-10, 10)

 

Scaling percentage

(-10, 10)