title: A textural approach based on Gabor functions for texture edge detection in ultrasound images.
abstract: Edge detection is an important, but difficult, step in quantitative ultrasound (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 detector using Gabor functions and a new texture-enhancement scheme. The experimental results on the synthetic edge images have shown that the performances of the four tested textural and nontextural edge detectors are about 20%-95% worse than that of the proposed approach. Moreover, the texture enhancement may improve the performance of the proposed texture edge detector by as much as 40%. The experiments on 20 clinical US images have shown that the proposed 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.
authors.affiliation: Institute of Biomedical Engineering, College of Medicine, National Taiwan University, Taipei, Taiwan. chung@lotus.mc.ntu.edu.tw
authors.forename: C M
authors.initials: CM
authors.lastname: Chen
authors.forename: H H
authors.initials: HH
authors.lastname: Lu
authors.forename: K C
authors.initials: KC
authors.lastname: Han
mesh_terms: D000465:Algorithms; D007089:Image Enhancement / Q000379:methods*; D008962:Models, Theoretical; D019047:Phantoms, Imaging; D014463:Ultrasonography / Q000379:methods*