Cephalometric landmarks detection is a knowledge intensive activity to identify on X-rays of the skull key points to perform measurements needed for medical diagnosis and treatment. We have elsewhere proposed CNNs (Cellular Neural Networks) to achieve an accuracy in automated landmarks detection suitable for clinical practice, and have applied the method for 8 landmarks located on the bone profile. This paper proposes and evaluates a CNNs approach augmented by local image dynamic enhancemet for other 3 landmarks that are notoriously difficult to locate; the advantages of this method in the landmark detection problem are pointed out.