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

Abstract 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.