A textural approach based on Gabor functions for texture edge detection inultrasound images

Edge detection is an important, but difficult, step in quantitative ultraso und (US) image analysis. In this paper, we present a new textural approach for detecting a class of edges in US images; namely, the texture edges with a weak regional mean gray-level difference (RMGD) between adjacent regions . The proposed approach comprises a vision model-based texture edge detecto r using Gabor functions and a new texture-enhancement scheme. The experimen tal results on the synthetic edge images have shown that the performances o f the four tested textural and nontextural edge detectors are about 20%-95% worse than that of the proposed approach. Moreover, the texture enhancemen t may improve the performance of the proposed texture edge detector by as m uch as 40%, The experiments on 20 clinical US images have shown that the pr oposed approach can find reasonable edges for real objects of interest with the performance of 0.4 +/- 0.08 in terms of the Pratt's figure. (C) 2001 W orld Federation for Ultrasound in Medicine & Biology.