Noise removal in medical mammography images using fast non-local means denoising algorithm for early breast cancer detection: a phantom study

作     者：Lee, Sungtaek Park, Seong Jin Jeon, Ji Min Lee, Mi-Hwa Ryu, Dae Yeon Lee, Eunbyeol Kang, Seong-Hyeon Lee, Youngjin 

作者机构：Eulji Univ Dept Radiol Sci 553 Sanseong Daero Seongnam Si Gyeonggi Do South Korea Ewha Womans Univ Dept Social Studies Educ 52 Ewhayeodae Gil Seoul South Korea Kyung Hee Univ hosp Gangdong Dept Radiol 892 Dongnam Ro Seoul South Korea Gachon Univ Dept Radiol Sci 191 Hambakmoero Incheon South Korea 

出 版 物：《OPTIK》 (光学)

年 卷 期：2019年第180卷

页      面：569-575页

核心收录：

学科分类：070207[理学-光学] 07[理学] 08[工学] 0803[工学-光学工程] 0702[理学-物理学] 

基　　金：National Research Foundation of Korea [NRF-2016R1D1A1B03930357] 

主　　题：Medial mammography Medical application Denoising algorithm Fast non-local means approach Image processing 

摘      要：Denoising plays a crucial role in the field of medical imaging in regard to the improvement of image quality. In this study, a fast nonlocal means (FNLM) denoising algorithm which utilizes neighborhood filtering is proposed and implemented for early breast cancer detection based on medical mammography. For comparison with conventional denoising methods, the Wiener filter and total variation (TV) denoising algorithm were used. The temporal resolution, coefficient of variation (COV), and contrast to noise ratio (CNR) were evaluated for three exposure conditions: (a) various tube voltages at fixed 40 mAs, (b) various tube currents at fixed 28 kVp, and (c) auto exposure control mode. The results showed that the proposed FNLM denoising algorithm can achieve a similar temporal resolution to the Wiener filter and may efficiently reduce image noise by using COV and CNR values in mammography.