超声微小血管成像杂波抑制技术综述

High-resolution, high-sensitivity, and real-time visualization of microvasculature has significant clinical application value in early diagnosis, intervention and treatment monitoring of cancer, coronary disease, cerebral small vessel disease and other diseases. One of the main challange of microvascular imaging is how to accurately separate blood flow signals from complex clutter information, and clutter suppression techniques have thus become an important research direction in the field of microvascular imaging. Several clutter suppression techniques currently used, including high-pass filtering, singular value decomposition (SVD), robust principal component analysis(RPCA), independent component analysis (ICA) and so on. In this article, we review the concepts, benefits, limitations and applications of clutter suppression techniques and consider their potential for further improvement in ultrasound microvascular imaging. The signal-to-noise ratio and sensitivity of ultrasonic microvascular imaging are thought to be further enhanced with constant innovation in clutter suppression techniques, providing major contributions to clinical applications.