Automated 3D region growing algorithm based on an assessment function

A new region growing algorithm is proposed for the automated segmentation o f three-dimensional images. No initial parameters such as the homogeneity t hreshold or the seeds location have to be adjusted. The principle of our me thod is to build a region growing sequence by increasing the maximal homoge neity threshold from a very small value to a large one. On each segmented r egion, a 3D parameter that has been validated on a test image assesses the segmentation quality. This set of values called assessment function is used to determine of the optimal homogeneity criterion. Our algorithm was teste d on 3D MR images for the segmentation of trabecular bone samples in order to quantify osteoporosis. A comparison to automated and manual thresholding showed that our algorithm performs better. Its main advantages are to elim inate isolated points due to the noise and to preserve connectivity of the bone structure. (C) 2002 Elsevier Science B.V. All rights reserved.