標題: A textural approach based on Gabor functions for texture edge detection in ultrasound images
作者: Chen, CM
Lu, HHS
Han, KC
統計學研究所
Institute of Statistics
關鍵字: ultrasound image;edge detection;early vision model;wavelet analysis;distance map;difference mask
公開日期: 1-Apr-2001
摘要: 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. (C) 2001 World Federation for Ultrasound in Medicine & Biology.
URI: http://dx.doi.org/10.1016/S0301-5629(00)00323-9
http://hdl.handle.net/11536/29729
ISSN: 0301-5629
DOI: 10.1016/S0301-5629(00)00323-9
期刊: ULTRASOUND IN MEDICINE AND BIOLOGY
Volume: 27
Issue: 4
起始頁: 515
結束頁: 534
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