A pipe-line method for multi-label segmentation of anatomic structures in a medical image by means of a convolutional neural network trained with a weighted loss function that takes into account under-representation of at least one anatomical structure in the ground-truth mask relative to other anatomical structures. Different architectures for the convolutional neural network are described.
MULTI-CLASS IMAGE SEGMENTATION METHOD