Adaptive clutter filtering for ultrasound color flow imaging

Area of Science:

• Medical Imaging
• Biomedical Engineering
• Signal Processing

Background:

• Conventional ultrasound color flow imaging uses a single clutter filter, which struggles with spatially and temporally varying clutter characteristics.
• This limitation hinders optimal clutter rejection and accurate blood flow velocity estimation.

Purpose of the Study:

• To develop and evaluate an adaptive clutter rejection method for ultrasound color flow imaging.
• The goal is to enhance the accuracy of blood flow velocity estimation by dynamically selecting clutter filters.

Main Methods:

• An adaptive clutter rejection method was developed, selecting filters at each image location based on clutter characteristics and filter properties.
• Filters evaluated include minimum-phase finite impulse response, projection-initialized infinite impulse response, and polynomial regression.
• The method was integrated into an ultrasound system for testing.

Main Results:

• The adaptive method significantly reduced the mean absolute error in velocity estimation compared to conventional single-filter techniques.
• An average gain of 5.0 dB in signal-to-clutter ratio (SCR) was achieved with in vivo abdominal data.
• The adaptive approach demonstrated improved SCR and reduced bias in flow velocity estimation.

Conclusions:

• The proposed adaptive clutter rejection method offers superior performance over conventional techniques in ultrasound color flow imaging.
• This method has the potential to significantly improve the accuracy of blood flow velocity estimation.
• Further improvements in SCR and bias reduction are key benefits of this adaptive approach.