Geometry guided radiograph segmentation

The author´s overall goal is to develop an image understanding system for automatically interpreting dental radiographs. A description is given of the module that integrates the intrinsic image data to form the region adjacency graph that represents the image. Classical segmentation algorithms will not always yield correct results, since blurred edges can cause adjacent anatomical regions to be labeled as one region. The authors´ solution is to guide the segmentation by intrinsic properties of the constituent objects, using a connected-components-like algorithm. Their experiments show that for dental radiographs a segmentation using gray-level data in conjunction with edges of the surfaces of teeth gives a robust and reliable segmentation.<>