{'fraction_non_alphanumeric': 0.01684717208182912, 'fraction_numerical': 0.0, 'mean_word_length': 5.208955223880597, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Improving axial resolution of medical ultrasound images by using noise-robust broadband filter based on singular value decomposition

Improving spatial resolution is a crucial issue in medical ultrasound. One of the improving methods is the post-processing of the received ultrasound RF signal. In the present paper, we proposed a design method for a noise-robust broadband filter based on the singular value decomposition of the received RF signal. To design a noise-robust filter, we proposed a logical method to determine the optimal truncated order of singular values, which was validated by applying the filter to noise-contaminated signals. Furthermore, the proposed filter applied to the wire phantom resulted in a better axial resolution than that obtained without the filter and with our previously designed Wiener filter.