For segmentation tasks with multiple classes, especially in the context of medical images where there might be class imbalance, is it preferable to use sigmoid or softmax as the final activation? I believe softmax would assign each particular pixel (voxel) to a single class whereas sigmoid could assign a single pixel (voxel) to multiple classes. Is this correct? Also, if we use dice loss as the loss function, are both softmax and sigmoid compatible or is one preferred over the other?