Craniofacial Landmark Detection by Layered Diffusion and Dilated Skeleton Maps

Abstract

Abstract-This paper proposed a new method for cephalogram landmark location. It firstly employed diffusions in different scales for layered segmentation, making uses of regionhomogeneity and edge-saltation, thus the landmark positions could be clearly reflected on edge-maps, i.e. skeleton, of layered diffusion. Secondly, key landmarks were determined via binarization pixel-cliques which were formed by Euclidean distance maps (EDM) on dilated skeleton. To validate the performance of this method, 30 surgery cases were inspected. The comparison of predicted parameters and application values shows that all 9 angle parameters and 4 of 5 distance parameters were correctly calculated, the predicted profiles were similar to the actual contours except one point due to the intrinsic difficulty in labium prediction. Our method took advantages of layered feature preserving and ease landmark extraction, and the latter was also owing to different EDM-Width of pixel-cliques and skeleton points. It is accurate, lifelike, and superior to many similar methods.

A novel strategy for automatic localization of cephalometric landmarks

“…Lihong Ma et.al. [11] proposed a novel approach to detect landmarks automatically, they use diffusion in different scales in layered segmentation, making uses of region homogeneity and edge saltation , so that the landmark position can be perfectly reflected on edge maps, i.e. skeleton, of layered diffusion.…”