Automatic landmarking of cephalograms by cellular neural networks

Cephalometric analysis is a time consuming measurement process by which experienced orthodontist identify on lateral craniofacial X-rays landmarks that are needed for diagnosis and treatment planning and evaluation. High speed and accuracy in detection of craniofacial landmarks are widely demanded. A prototyped system, which is based on CNNs (Cellular Neural Networks) is proposed as an efficient technique for landmarks detection. The first stage of system evaluation assessed the image output of the CNN, to verify that it included and properly highlighted the sought landmark. The second stage evaluated performance of the developed algorithms for 8 landmarks. Compared with the other methods proposed in the literature, the findings are particularly remarkable with respect to the accuracy obtained. Another advantage of a CNN based system is that the method can either be implemented via software, or directly embedded in the hardware, for real-time performance.