Noise reduction in ultrasound images

Abstract

Systems and methods for noise reduction in ultrasound images are described. These systems and methods include a noise-reduction system that provides a tensor-based approach that mitigates effects of noise processes on ultrasound images and produces 'preprocessed' ultrasound images having consistent characteristics, which increases the accuracy and effectiveness of further processing (e.g., via detection and/or segmentation algorithms) of the ultrasound images. In aspects, these techniques enable neural networks, coupled to the noise-reduction system, to generate consistent inferences across different ultrasound images, thereby enhancing a workflow and user experience of an ultrasound operator. Using these techniques further enables the neural networks to be trained with fewer training images, saving time and monetary costs without sacrificing accuracy. State information of the noise-reduction system, corresponding to when the preprocessed ultrasound images are generated, can also be used to configure the neural networks, resulting in more-efficient operation and resource utilization.