seg_liver.py 文件源码

def class_balanced_cross_entropy_loss(output, label):
    """Define the class balanced cross entropy loss to train the network
    Args:
    output: Output of the network
    label: Ground truth label
    Returns:
    Tensor that evaluates the loss

    """

    labels = tf.cast(tf.greater(label, 0.5), tf.float32)

    output_gt_zero = tf.cast(tf.greater_equal(output, 0), tf.float32)

    loss_val = tf.multiply(output, (labels - output_gt_zero)) - tf.log(
        1 + tf.exp(output - 2 * tf.multiply(output, output_gt_zero)))

    loss_pos = tf.reduce_sum(-tf.multiply(labels, loss_val))
    loss_neg = tf.reduce_sum(-tf.multiply(1.0 - labels, loss_val))

    final_loss = 0.931 * loss_pos + 0.069 * loss_neg

    return final_loss