| import tensorflow as tf | |
| from tensorflow.keras import backend as K | |
| def boundary_loss(y_true, y_pred): | |
| """Additional loss focusing on boundaries""" | |
| # Compute gradients | |
| dy_true, dx_true = tf.image.image_gradients(y_true) | |
| dy_pred, dx_pred = tf.image.image_gradients(y_pred) | |
| # Compute boundary loss | |
| loss = tf.reduce_mean(tf.abs(dy_pred - dy_true) + tf.abs(dx_pred - dx_true)) | |
| return loss * 0.5 # weight factor | |
| def enhanced_binary_crossentropy(y_true, y_pred): | |
| """Combine standard BCE with boundary loss""" | |
| bce = tf.keras.losses.binary_crossentropy(y_true, y_pred) | |
| boundary = boundary_loss(y_true, y_pred) | |
| return bce + boundary |