Chen, Chung-MingChung-MingChenLu, Henry Horng-ShingHenry Horng-ShingLuHan, Ko-ChungKo-ChungHan2009-02-182018-06-292009-02-182018-06-29200103015629http://ntur.lib.ntu.edu.tw//handle/246246/132693https://www.scopus.com/inward/record.uri?eid=2-s2.0-0035012295&doi=10.1016%2fS0301-5629%2800%2900323-9&partnerID=40&md5=45e700ea17054fac0602b9193f9d0049Edge 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. (E-mail: chung@lotus.mc.ntu.edu.tw) Copyright © 2001 World Federation for Ultrasound in Medicine & Biology.application/pdf1072212 bytesapplication/pdfen-USDifference mask; Distance map; Early vision model; Edge detection; Ultrasound image; Wavelet analysisEdge detection; Image analysis; Textures; Texture edge detection; Ultrasonic imaging; algorithm; article; image analysis; priority journal; ultrasound; Algorithms; Image Enhancement; Models, Theoretical; Phantoms, Imaging; Ultrasonography10.1016/S0301-5629(00)00323-9113688642-s2.0-0035012295http://ntur.lib.ntu.edu.tw/bitstream/246246/132693/1/05.pdf