Ultrasound Image Despeckling Using Stochastic Distance-Based BM3D

作     者：Santos, Cid A. N. Martins, Diego L. N. Mascarenhas, Nelson D. A. 

作者机构：Univ Fed Sao Carlos Dept Comp BR-13565905 Sao Carlos Brazil Israelite Hosp Albert Einstein Dept Intervent Radiol BR-05651901 Sao Paulo Brazil Fac Campo Limpo Paulista BR-13231230 Campo Limpo Paulista Brazil 

出 版 物：《IEEE TRANSACTIONS ON IMAGE PROCESSING》 (IEEE Trans Image Process)

年 卷 期：2017年第26卷第6期

页      面：2632-2643页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Despeckling ultrasound imaging stochastic distances BM3D patch-based filtering 

摘      要：Ultrasound image despeckling is an important research field, since it can improve the interpretability of one of the main categories of medical imaging. Many techniques have been tried over the years for ultrasound despeckling, and more recently, a great deal of attention has been focused on patch-based methods, such as non-local means and block-matching collaborative filtering (BM3D). A common idea in these recent methods is the measure of distance between patches, originally proposed as the Euclidean distance, for filtering additive white Gaussian noise. In this paper, we derive new stochastic distances for the Fisher-Tippett distribution, based on well-known statistical divergences, and use them as patch distance measures in a modified version of the BM3D algorithm for despeckling log-compressed ultrasound images. State-of-the-art results in filtering simulated, synthetic, and real ultrasound images confirm the potential of the proposed approach.